how to make speech recognition in javascript

JavaScript Speech Recognition Example (Speech to Text)

With the Web Speech API, we can recognize speech using JavaScript . It is super easy to recognize speech in a browser using JavaScript and then getting the text from the speech to use as user input. We have already covered How to convert Text to Speech in Javascript .

But the support for this API is limited to the Chrome browser only . So if you are viewing this example in some other browser, the live example below might not work.

Javascript speech recognition - speech to text

This tutorial will cover a basic example where we will cover speech to text. We will ask the user to speak something and we will use the SpeechRecognition object to convert the speech into text and then display the text on the screen.

The Web Speech API of Javascript can be used for multiple other use cases. We can provide a list of rules for words or sentences as grammar using the SpeechGrammarList object, which will be used to recognize and validate user input from speech.

For example, consider that you have a webpage on which you show a Quiz, with a question and 4 available options and the user has to select the correct option. In this, we can set the grammar for speech recognition with only the options for the question, hence whatever the user speaks, if it is not one of the 4 options, it will not be recognized.

We can use grammar, to define rules for speech recognition, configuring what our app understands and what it doesn't understand.

JavaScript Speech to Text

In the code example below, we will use the SpeechRecognition object. We haven't used too many properties and are relying on the default values. We have a simple HTML webpage in the example, where we have a button to initiate the speech recognition.

The main JavaScript code which is listening to what user speaks and then converting it to text is this:

In the above code, we have used:

recognition.start() method is used to start the speech recognition.

Once we begin speech recognition, the onstart event handler can be used to inform the user that speech recognition has started and they should speak into the mocrophone.

When the user is done speaking, the onresult event handler will have the result. The SpeechRecognitionEvent results property returns a SpeechRecognitionResultList object. The SpeechRecognitionResultList object contains SpeechRecognitionResult objects. It has a getter so it can be accessed like an array. The first [0] returns the SpeechRecognitionResult at the last position. Each SpeechRecognitionResult object contains SpeechRecognitionAlternative objects that contain individual results. These also have getters so they can be accessed like arrays. The second [0] returns the SpeechRecognitionAlternative at position 0 . We then return the transcript property of the SpeechRecognitionAlternative object.

Same is done for the confidence property to get the accuracy of the result as evaluated by the API.

We have many event handlers, to handle the events surrounding the speech recognition process. One such event is onspeechend , which we have used in our code to call the stop() method of the SpeechRecognition object to stop the recognition process.

Now let's see the running code:

When you will run the code, the browser will ask for permission to use your Microphone , so please click on Allow and then speak anything to see the script in action.

Conclusion:

So in this tutorial we learned how we can use Javascript to write our own small application for converting speech into text and then displaying the text output on screen. We also made the whole process more interactive by using the various event handlers available in the SpeechRecognition interface. In future I will try to cover some simple web application ideas using this feature of Javascript to help you usnderstand where we can use this feature.

If you face any issue running the above script, post in the comment section below. Remember, only Chrome browser supports it .

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Web Speech API

Baseline widely available.

This feature is well established and works across many devices and browser versions. It’s been available across browsers since September 2018 .

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The Web Speech API enables you to incorporate voice data into web apps. The Web Speech API has two parts: SpeechSynthesis (Text-to-Speech), and SpeechRecognition (Asynchronous Speech Recognition.)

Web Speech Concepts and Usage

The Web Speech API makes web apps able to handle voice data. There are two components to this API:

Speech recognition is accessed via the SpeechRecognition interface, which provides the ability to recognize voice context from an audio input (normally via the device's default speech recognition service) and respond appropriately. Generally you'll use the interface's constructor to create a new SpeechRecognition object, which has a number of event handlers available for detecting when speech is input through the device's microphone. The SpeechGrammar interface represents a container for a particular set of grammar that your app should recognize. Grammar is defined using JSpeech Grammar Format ( JSGF .)
Speech synthesis is accessed via the SpeechSynthesis interface, a text-to-speech component that allows programs to read out their text content (normally via the device's default speech synthesizer.) Different voice types are represented by SpeechSynthesisVoice objects, and different parts of text that you want to be spoken are represented by SpeechSynthesisUtterance objects. You can get these spoken by passing them to the SpeechSynthesis.speak() method.

For more details on using these features, see Using the Web Speech API .

Web Speech API Interfaces

Speech recognition.

The controller interface for the recognition service; this also handles the SpeechRecognitionEvent sent from the recognition service.

Represents a single word that has been recognized by the speech recognition service.

Represents error messages from the recognition service.

The event object for the result and nomatch events, and contains all the data associated with an interim or final speech recognition result.

The words or patterns of words that we want the recognition service to recognize.

Represents a list of SpeechGrammar objects.

Represents a single recognition match, which may contain multiple SpeechRecognitionAlternative objects.

Represents a list of SpeechRecognitionResult objects, or a single one if results are being captured in continuous mode.

Speech synthesis

The controller interface for the speech service; this can be used to retrieve information about the synthesis voices available on the device, start and pause speech, and other commands besides.

Contains information about any errors that occur while processing SpeechSynthesisUtterance objects in the speech service.

Contains information about the current state of SpeechSynthesisUtterance objects that have been processed in the speech service.

Represents a speech request. It contains the content the speech service should read and information about how to read it (e.g. language, pitch and volume.)

Represents a voice that the system supports. Every SpeechSynthesisVoice has its own relative speech service including information about language, name and URI.

Specified out as part of a [NoInterfaceObject] interface called SpeechSynthesisGetter , and Implemented by the Window object, the speechSynthesis property provides access to the SpeechSynthesis controller, and therefore the entry point to speech synthesis functionality.

For information on errors reported by the Speech API (for example, "language-not-supported" and "language-unavailable" ), see the following documentation:

error property of the SpeechRecognitionErrorEvent object
error property of the SpeechSynthesisErrorEvent object

The Web Speech API examples on GitHub contains demos to illustrate speech recognition and synthesis.

Specifications

Specification

Browser compatibility

Api.speechrecognition.

BCD tables only load in the browser with JavaScript enabled. Enable JavaScript to view data.

api.SpeechSynthesis

Using the Web Speech API
SitePoint article
HTML5Rocks article

JavaScript Speech Recognition

Speech Recognition is a broad term that is often associated solely with Speech-to-Text technology. However, Speech Recognition can also include technologies such as Wake Word Detection , Voice Command Recognition , and Voice Activity Detection ( VAD ).

This article provides a thorough guide on integrating on-device Speech Recognition into JavaScript Web apps. We will be learning about the following technologies:

Cobra Voice Activity Detection

Porcupine Wake Word

Rhino speech-to-intent, cheetah streaming speech-to-text, leopard speech-to-text.

In addition to plain JavaScript, Picovoice's Speech Recognition engines are also available in different UI frameworks such as React , Angular , and Vue .

Cobra Voice Activity Detection is a VAD engine that can be used to detect the presence of human speech within an audio signal.

Install the Web Voice Processor and Cobra Voice Activity Detection Web SDK packages using npm :

Sign up for a free Picovoice Console account and copy your AccessKey from the main dashboard. The AccessKey is only required for authentication and authorization.

Create an instance of CobraWorker :

Subscribe CobraWorker to WebVoiceProcessor to start processing audio frames:

For further details, visit the Cobra Voice Activity Detection product page or refer to the Cobra Web SDK quick start guide .

Porcupine Wake Word is a wake word detection engine that can be used to listen for user-specified keywords and activate dormant applications when a keyword is detected.

Install the Web Voice Processor and Porcupine Wake Word Web SDK packages using npm :

Create and download a custom Wake Word model using Picovoice Console.

Add the Porcupine model ( .pv ) for your language of choice and your custom Wake Word model ( .ppn ) created in the previous step to the project's public directory:

Create objects containing the Porcupine model and Wake Word model options:
Create an instance of PorcupineWorker :
Subscribe PorcupineWorker to WebVoiceProcessor to start processing audio frames:

For further details, visit the Porcupine Wake Word product page or refer to the Porcupine Web SDK quick start guide .

Rhino Speech-to-Intent is a voice command recognition engine that infers user intents from utterances, allowing users to interact with applications via voice.

Install the Web Voice Processor and Rhino Speech-to-Intent Web SDK packages using npm :

Create your Context using Picovoice Console.

Add the Rhino Speech-to-Intent model ( .pv ) for your language of choice and the Context model ( .rhn ) created in the previous step to the project's public directory:

Create an object containing the Rhino Speech-to-Intent model and Context model options:
Create an instance of RhinoWorker :
Subscribe RhinoWorker to WebVoiceProcessor to start processing audio frames:

For further details, visit the Rhino Speech-to-Intent product page or refer to the Rhino's Web SDK quick start guide .

Cheetah Streaming Speech-to-Text is a speech-to-text engine that transcribes voice data in real time, synchronously with audio generation.

Install the Web Voice Processor and Cheetah Streaming Speech-to-Text Web SDK packages using npm :

Generate a custom Cheetah Streaming Speech-to-Text model from the Picovoice Console ( .pv ) or download the default model ( .pv ).

Add the model to the project's public directory:

Create an object containing the model options:
Create an instance of CheetahWorker :
Subscribe CheetahWorker to WebVoiceProcessor to start processing audio frames:

For further details, visit the Cheetah Streaming Speech-to-Text product page or refer to the Cheetah Web SDK quick start guide .

In contrast to Cheetah Streaming Speech-to-Text , Leopard Speech-to-Text waits for the complete spoken phrase to complete before providing a transcription, enabling higher accuracy and runtime efficiency.

Install the Leopard Speech-to-Text Web SDK package using npm :

Generate a custom Leopard Speech-to-Text model ( .pv ) from Picovoice Console or download a default model ( .pv ) for the language of your choice.

Create an instance of LeopardWorker :
Transcribe audio (sample rate of 16 kHz, 16-bit linearly encoded and 1 channel):

For further details, visit the Leopard Speech-to-Text product page or refer to Leopard's Web SDK quick start guide .

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JavaScript Text-to-Speech - The Easy Way

Learn how to build a simple JavaScript Text-to-Speech application using JavaScript's Web Speech API in this step-by-step beginner's guide.

Contributor

When building an app, you may want to implement a Text-to-Speech feature for accessibility, convenience, or some other reason. In this tutorial, we will learn how to build a very simple JavaScript Text-to-Speech application using JavaScript's built-in Web Speech API .

For your convenience, we have provided the code for this tutorial application ready for you to fork and play around with over at Replit , or ready for you to clone from Github . You can also view a live version of the app here .

Step 1 - Setting Up The App

First, we set up a very basic application using a simple HTML file called index.html and a JavaScript file called script.js .

We'll also use a CSS file called style.css to add some margins and to center things, but it’s entirely up to you if you want to include this styling file.

The HTML file index.html defines our application's structure which we will add functionality to with the JavaScript file. We add an <h1> element which acts as a title for the application, an <input> field in which we will enter the text we want spoken, and a <button> which we will use to submit this input text. We finally wrap all of these objects inside of a <form> . Remember, the input and the button have no functionality yet - we'll add that in later using JavaScript.

Inside of the <head> element, which contains metadata for our HTML file, we import style.css . This tells our application to style itself according to the contents of style.css . At the bottom of the <body> element, we import our script.js file. This tells our application the name of the JavaScript file that stores the functionality for the application.

Now that we have finished the index.html file, we can move on to creating the script.js JavaScript file.

Since we imported the script.js file to our index.html file above, we can test its functionality by simply sending an alert .

To add an alert to our code, we add the line of code below to our script.js file. Make sure to save the file and refresh your browser, you should now see a little window popping up with the text "It works!".

If everything went ok, you should be left with something like this:

Step 2 - Checking Browser Compatibility

To create our JavaScript Text-to-Speech application, we are going to utilize JavaScript's built-in Web Speech API. Since this API isn’t compatible with all browsers, we'll need to check for compatibility. We can perform this check in one of two ways.

The first way is by checking our operating system and version on caniuse.com .

The second way is by performing the check right inside of our code, which we can do with a simple conditional statement:

This is a shorthand if/else statement, and is equivalent to the following:

If you now run the app and check your browser console, you should see one of those messages. You can also choose to pass this information on to the user by rendering an HTML element.

Step 3 - Testing JavaScript Text-to-Speech

Next up, let’s write some static code to test if we can make the browser speak to us.

Add the following code to the script.js file.

Code Breakdown

Let’s look at a code breakdown to understand what's going on:

With const synth = window.speechSynthesis we declare the synth variable to be an instance of the SpeechSynthesis object, which is the entry to point to using JavaScript's Web Speech API. The speak method of this object is what ultimately converts text into speech.
let ourText = “Hey there what’s up!!!!” defines the ourText variable which holds the string of text that we want to be uttered.
const utterThis = new SpeechSynthesisUtterance(ourText) defines the utterThis variable to be a SpeechSynthesisUtterance object, into which we pass ourText .
Putting it all together, we call synth.speak(utterThis) , which utters the string inside ourText .

Save the code and refresh the browser window in which your app runs in order to hear a voice saying “ Hey there what’s up!!!! ”.

Step 4 - Making Our App Dynamic

Our code currently provides us with a good understanding of how the Text-to-Speech aspect of our application works under the hood, but the app at this point only converts the static text which we defined with ourText into speech. We want to be able to dynamically change what text is being converted to speech when using the application. Let’s do that now utilizing a <form> .

First, we add the const textInputField = document.querySelector("#text-input") variable, which allows us to access the value of the <input> tag that we have defined in the index.html file in our JavaScript code. We select the <input> field by its id: #text-input .
Secondly, we add the const form = document.querySelector("#form") variable, which selects our form by its id #form so we can later submit the <form> using the onsubmit function.
We initialize ourText as an empty string instead of a static sentence.
We wrap our browser compatibility logic in a function called checkBrowserCompatibility and then immediately call this function.

Finally, we create an onsubmit handler that executes when we submit our form. This handler does several things:

event.preventDefault() prevents the browser from reloading after submitting the form.
ourText = textInputField.value sets our ourText string to whatever we enter in the "input" field of our application.
utterThis.text = ourText sets the text to be uttered to the value of ourText .
synth.speak(utterThis) utters our text string.
textInputField.value resets the value of our input field to an empty string after submitting the form.

Step 5 - Testing Our JavaScript Text-to-Speech App

To test our JavaScript Text-to-Speech application, simply enter some text in the input field and hit “Submit” in order to hear the text converted to speech.

Additional Features

There are a lot of properties that can be modified when working with the Web Speech API. For instance:

You can try playing around with these properties to tailor the application to your needs.

This simple example provides an outline of how to use the Web Speech API for JavaScript Text-to-Speech .

While Text-to-Speech is useful for accessibility, convenience, and other purposes, there are a lot of use-cases in which the opposite functionality, i.e. Speech-to-Text, is useful. We have built a couple of example projects using AssemblyAI’s Speech-to-Text API that you can check out for those who want to learn more.

Some of them are:

React Speech Recognition with React Hooks
How To Convert Voice To Text Using JavaScript

AI trends in 2024: Graph Neural Networks

Developer Educator at AssemblyAI

AI for Universal Audio Understanding: Qwen-Audio Explained

Combining Speech Recognition and Diarization in one model

How DALL-E 2 Actually Works

Español – América Latina
Português – Brasil
Tiếng Việt
Chrome for Developers

Voice driven web apps - Introduction to the Web Speech API

The new JavaScript Web Speech API makes it easy to add speech recognition to your web pages. This API allows fine control and flexibility over the speech recognition capabilities in Chrome version 25 and later. Here's an example with the recognized text appearing almost immediately while speaking.

DEMO / SOURCE

Let’s take a look under the hood. First, we check to see if the browser supports the Web Speech API by checking if the webkitSpeechRecognition object exists. If not, we suggest the user upgrades their browser. (Since the API is still experimental, it's currently vendor prefixed.) Lastly, we create the webkitSpeechRecognition object which provides the speech interface, and set some of its attributes and event handlers.

The default value for continuous is false, meaning that when the user stops talking, speech recognition will end. This mode is great for simple text like short input fields. In this demo , we set it to true, so that recognition will continue even if the user pauses while speaking.

The default value for interimResults is false, meaning that the only results returned by the recognizer are final and will not change. The demo sets it to true so we get early, interim results that may change. Watch the demo carefully, the grey text is the text that is interim and does sometimes change, whereas the black text are responses from the recognizer that are marked final and will not change.

To get started, the user clicks on the microphone button, which triggers this code:

We set the spoken language for the speech recognizer "lang" to the BCP-47 value that the user has selected via the selection drop-down list, for example “en-US” for English-United States. If this is not set, it defaults to the lang of the HTML document root element and hierarchy. Chrome speech recognition supports numerous languages (see the “ langs ” table in the demo source), as well as some right-to-left languages that are not included in this demo, such as he-IL and ar-EG.

After setting the language, we call recognition.start() to activate the speech recognizer. Once it begins capturing audio, it calls the onstart event handler, and then for each new set of results, it calls the onresult event handler.

This handler concatenates all the results received so far into two strings: final_transcript and interim_transcript . The resulting strings may include "\n", such as when the user speaks “new paragraph”, so we use the linebreak function to convert these to HTML tags <br> or <p> . Finally it sets these strings as the innerHTML of their corresponding <span> elements: final_span which is styled with black text, and interim_span which is styled with gray text.

interim_transcript is a local variable, and is completely rebuilt each time this event is called because it’s possible that all interim results have changed since the last onresult event. We could do the same for final_transcript simply by starting the for loop at 0. However, because final text never changes, we’ve made the code here a bit more efficient by making final_transcript a global, so that this event can start the for loop at event.resultIndex and only append any new final text.

That’s it! The rest of the code is there just to make everything look pretty. It maintains state, shows the user some informative messages, and swaps the GIF image on the microphone button between the static microphone, the mic-slash image, and mic-animate with the pulsating red dot.

The mic-slash image is shown when recognition.start() is called, and then replaced with mic-animate when onstart fires. Typically this happens so quickly that the slash is not noticeable, but the first time speech recognition is used, Chrome needs to ask the user for permission to use the microphone, in which case onstart only fires when and if the user allows permission. Pages hosted on HTTPS do not need to ask repeatedly for permission, whereas HTTP hosted pages do.

So make your web pages come alive by enabling them to listen to your users!

We’d love to hear your feedback...

For comments on the W3C Web Speech API specification: email , mailing archive , community group
For comments on Chrome’s implementation of this spec: email , mailing archive

Refer to the Chrome Privacy Whitepaper to learn how Google is handling voice data from this API.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License , and code samples are licensed under the Apache 2.0 License . For details, see the Google Developers Site Policies . Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2013-01-13 UTC.

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Getting started with the Speech Recognition API in Javascript

Carlos Delgado

January 22, 2017
27.4K views

Learn how to use the speech recognition API with Javascript in Google Chrome

The JavaScript API Speech Recognition enables web developers to incorporate speech recognition into your web page. This API allows fine control and flexibility over the speech recognition capabilities in Chrome version 25 and later. This API is experimental, that means that it's not available on every browser. Even in Chrome, there are some attributes of the API that aren't supported. For more information visit Can I Use Speech Recognition .

In this article you will learn how to use the Speech Recognition API, in its most basic expression.

Implementation

To get started, you will need to know wheter the browser supports the API or not. To do this, you can verify if the window object in the browser has the webkitSpeechRecognition property using any of the following snippets:

Once you verify, you can start to work with this API. Create a new instance of the webkitSpeechRecognition class and set the basic properties:

Now that the basic options are set, you will need to add some event handlers. In this case we are going add the basic listeners as onerror , onstart , onend and onresult (event used to retrieve the recognized text).

The onresult event receives as first parameter a custom even object. The results are stored in the event.results property (an object of type SpeechRecognitionResultList that stores the SpeechRecognitionResult objects, this in turn contains instances of SpeechRecognitionAlternative with the transcript property that contains the text ).

As the final step, you need to start it by executing the start method of the recognition object or to stop it once it's running executing the stop method:

Now the entire functional snippet to use the speech recognition API should look like:

Once you execute the start method, the microphone permission dialog will be shown in the Browser.

Go ahead and test it in your web or local server. You can see a live demo of the Speech Recognition API working in the browser in all the available languages from the official Chrome Demos here .

Supported languages

Currently, the API supports 40 languages in Chrome. Some languages have specifical codes according to the region (the identifiers follow the BCP-47 format ):

Language	Region	Language code
Afrikaans	Default	af-ZA
Bahasa Indonesia	Default	id-ID
Bahasa Melayu	Default	ms-MY
Català	Default	ca-ES
Äeština	Default	cs-CZ
Dansk	Default	da-DK
Deutsch	Default	de-DE
English	Australia	en-AU
English	Canada	en-CA
English	India	en-IN
English	New Zealand	en-NZ
English	South Africa	en-ZA
English	United Kingdom	en-GB
English	United States	en-US
Español	Argentina	es-AR
Español	Bolivia	es-BO
Español	Chile	es-CL
Español	Colombia	es-CO
Español	Costa Rica	es-CR
Español	Ecuador	es-EC
Español	El Salvador	es-SV
Español	España	es-ES
Español	Estados Unidos	es-US
Español	Guatemala	es-GT
Español	Honduras	es-HN
Español	México	es-MX
Español	Nicaragua	es-NI
Español	Panamá	es-PA
Español	Paraguay	es-PY
Español	Perú	es-PE
Español	Puerto Rico	es-PR
Español	República Dominicana	es-DO
Español	Uruguay	es-UY
Español	Venezuela	es-VE
Euskara	Default	eu-ES
Filipino	Default	fil-PH
Français	Default	fr-FR
Galego	Default	gl-ES
Hrvatski	Default	hr_HR
IsiZulu	Default	zu-ZA
Íslenska	Default	is-IS
Italiano	Italia	it-IT
Italiano	Svizzera	it-CH
LietuviÅ³	Default	lt-LT
Magyar	Default	hu-HU
Nederlands	Default	nl-NL
Norsk bokmål	Default	nb-NO
Polski	Default	pl-PL
Português	Brasil	pt-BR
Português	Portugal	pt-PT
RomânÄ	Default	ro-RO
SlovenšÄina	Default	sl-SI
SlovenÄina	Default	sk-SK
Suomi	Default	fi-FI
Svenska	Default	sv-SE
Tiáº¿ng Viá»t	Default	vi-VN
Türkçe	Default	tr-TR
ΕλληνικÎ¬	Default	el-GR
Ð±ÑÐ»Ð³Ð°ÑÑÐºÐ¸	Default	bg-BG
PÑÑÑÐºÐ¸Ð¹	Default	ru-RU
Ð¡ÑÐ¿ÑÐºÐ¸	Default	sr-RS
Ð£ÐºÑÐ°ÑÐ½ÑÑÐºÐ°	Default	uk-UA
íêµì´	Default	ko-KR
ä¸æ	æ®éè¯ (ä¸å½å¤§é)	cmn-Hans-CN
ä¸æ	æ®éè¯ (é¦æ¸¯)	cmn-Hans-HK
ä¸æ	ä¸æ (å°ç£)	cmn-Hant-TW
ä¸æ	ç²µèª (é¦æ¸¯)	yue-Hant-HK
æ¥æ¬èª	Default	ja-JP
à¤¹à¤¿à¤¨à¥à¤¦à¥	Default	hi-IN
à¸ à¸²à¸©à¸²à¹à¸à¸¢	Default	th-TH

You can use the following object if you need the previous table in Javascript and you can iterate it as shown in the example:

Whose output in the console will be:

Happy coding !

Senior Software Engineer at Software Medico . Interested in programming since he was 14 years old, Carlos is a self-taught programmer and founder and author of most of the articles at Our Code World.

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Recognizing Speech with vanilla JavaScript

Aug 12, 2022 · 5 min read

Recognizing Speech with vanilla JavaScript

Before we start our project, I’d like to discuss the concept of speech recognition. What is speech recognition? Speech recognition, also known as automatic speech recognition (ASR), computer speech recognition, or speech-to-text, is a capability that enables a program to process human speech into a written format . In today’s world, big companies, especially big tech companies, use AI’s such as Alexa, Cortana, Google Assistant, and Siri, which all have the Speech recognition feature, a key component of their performance.

In this tutorial, we will learn how to use JavaScript to add a speech recognition feature to any web app. We will be using the speech recognition Webkit API to achieve this; the chat app should look and function like this:

The chat app will be able to access your microphone when the start listening button is clicked and will have a response to specific questions asked. The chat app is only available on a few browsers on Desktop and Android.

Web Speech API is used to incorporate voice data into web apps. It provides two distinct areas of functionality — speech recognition and speech synthesis (also known as text to speech, or TTS) — which open up interesting new possibilities for accessibility and control mechanisms. It receives speech through a device’s microphone, which is then checked by a speech recognition service against a list of grammar. When a word or phrase is successfully recognized, it returns a result or results as a text string, and other actions can be launched as a result or results.

So to get started, we need to create a chat section structure with HTML and style it with CSS. Our primary focus is on the functionality of the chat section so that you can get the HTML structure and CSS styling in my GitHub repository or for practice purposes, you can create and style a chat section of your choice and follow along for the functionalities in this article.

Setting Up our JavaScript file

Head straight into the JS section, the first thing to do is grab a text container where all messages and replies will be in and the buttons that start and stop the speech recognition process, and then we set up the window speech recognition WebKit API . After setting that up, we will create a variable that will store the speech recognition constructor and set the interim results to true.

The interim results seen on line 10 allow us to get the results when we speak, so it is something like real-time. If we set it to false, it will simply wait till we are done speaking and then return the result, but for this tutorial, we want to have our results while we speak.

After setting up the window WebKit above, we can create a new element. We will create a p tag, then create an event listener below for our recognition and pass in (e) as a parameter and log (e), so we can test what we have done so far.

We added recognition.start on line 9 to allow the web browser to start listening. When you head to the web browser and hit the refresh button, you should get a pop-up request to allow your microphone access. Click on the allow button and open your browser’s terminal while you speak. You will observe that while you speak, you’ll get some events in your terminal, and if you open any of them, you’ll see some options, including results, which we need. If you also look closely, you’d observe that most events have a length of 1 while some have a length of 2. If you open the results property with a length of 2, you’d see it contains two separate words like in the picture below.

Looking at the image above, it has a length of 2 because it contains two words that I highlighted. The words are meant to be in a single sentence, and to correct that we will need to map through each of our results and put them together in one sentence. For that to happen, we will make a variable; let’s call it texts. Then we need to make the results property an array. We’ll use Array. from and then insert (e.results), and that will give us an array.

Now we need to map through the results array and target the first speech recognition result, which has an index of zero. Then we target the transcript property that holds the words, map them through, and then join both transcripts to put both words together in a sentence. If you log text and head to the terminal in your browser and start speaking, you will see our words are forming sentences, although it is not 100% accurate yet.

Open Source Session Replay

OpenReplay is an open-source, session replay suite that lets you see what users do on your web app, helping you troubleshoot issues faster. OpenReplay is self-hosted for full control over your data.

Start enjoying your debugging experience - start using OpenReplay for free .

Adding our speech to our chat section

Now that we have successfully shown the sentences in our terminal, we need to add them to our chat section. To show them in the chat section, we need to add the text variable from above to the p tag we created earlier. Then we append it to a container div element that holds the p tag in our HTML. If you check your web browser, you’d see our results are now showing in the chat section, but there is a problem. If you start speaking again, it will keep adding the sentences to just one paragraph. This is because we need to start over a new session in a new paragraph when the first session ends.

To resolve this, we will need to create an event listener with an “end” event to stop the last session and a function containing a recognition start, to begin a new session. If you speak in your browser, you will still notice that new sentences or words are overriding the old sentences or words contained in the paragraph tag, and we don’t want that too. To handle this, we also need to create a new paragraph for a new session, but before we do that, we will need to change the isFinal value, as seen below.

The isFinal property is located in the speech recognition results as seen above. It is set to false by default, meaning we are in our current session, and whenever it is true, we have ended that session. So going back to our code, we will need to check the isFinal results with a conditional statement, as seen below. When we set the isFinal property to true, a new paragraph tag will be added below with the content of the new session, and that is all.

Adding some Custom replies to our Chat-app

We have successfully set up our chat app to listen with our browser’s microphone and display what was heard in written format. I will also show you how to set the buttons to start and stop the listening process below. We can also do something exciting and create custom replies based on the texts displayed. To do this, we will have to go into our last conditional statement before the p tag and add another conditional statement. This will check if the text variable we created earlier contains a particular word like “hello”. If true, we can create a p tag, give it a class name for styling and then add a custom reply to the p tag.

We can also perform specific tasks like opening another page and a lot more. I have added a couple of replies to my code below.

The window method , as seen above, is a JS method that tells the browser to open a certain path or link. Ensure you maintain the letter casing while setting your task if needed. Once all is done, if you head to your browser and speak, for instance, say “open a YouTube page”, you should be redirected to a random page on YouTube in your browser. If this doesn’t work, check your browser settings and allow page pop-ups, which should then work. So when the start button is clicked, the chat app starts the listening process, and when the stop button is clicked, it aborts the current session.

In this tutorial, we have successfully created a chat app that listens and translates what’s heard into text format. This can be used to perform different tasks like responding with custom replies and assisting in page redirections by implementing speech recognition using JavaScript. To improve on this, feel free to challenge yourself using the speech recognition API to perform complex tasks and projects like creating a translator or a mini Ai with custom replies.

GitHub repo: https://github.com/christofa/Speech-recognition-chat-app.git

A TIP FROM THE EDITOR: For solutions specific to React, don’t miss our Make your app speak with React-Speech-kit and Voice enabled forms in React with Speechly articles.

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How to convert speech into text using JavaScript ?

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Converting Text to Speech in Java
How to Convert Text to Speech in Android using Kotlin?
Convert Text to Speech in Python
Text to speech GUI convertor using Tkinter in Python

In this article, we will learn to convert speech into text using HTML and JavaScript.

Approach: We added a content editable “div” by which we make any HTML element editable.

We use the SpeechRecognition object to convert the speech into text and then display the text on the screen.

We also added WebKit Speech Recognition to perform speech recognition in Google chrome and Apple safari.

InterimResults results should be returned true and the default value of this is false. So set interimResults= true

Use appendChild() method to append a node as the last child of a node.

Add eventListener, in this event listener, map() method is used to create a new array with the results of calling a function for every array element.

Note: This method does not change the original array.

Use join() method to return array as a string.

Final Code:

Output:

If the user tells “Hello World” after running the file, it shows the following on the screen.

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Simple Voice Search Using Javascript Speech Recognition

Table of contents, javascript voice search, voice search demo, part 1) the html.

This should be very straightforward. Pretty much a “regular search form” with an additional voice search button.

PART 2) THE JAVASCRIPT

Download & notes, sorry for the ads....

But someone has to pay the bills, and sponsors are paying for it. I insist on not turning Code Boxx into a "paid scripts" business, and I don't "block people with Adblock". Every little bit of support helps.

EXAMPLE CODE DOWNLOAD

Extra bits & links, i want nice search icons.

I have deliberately left an “ugly search form” to make it easy for people to customize… Feel free to use whatever framework you like. For the guys who are new, check out:

HOW TO SEARCH!?

Compatibility checks.

Speech recognition is only available on Chrome, Edge, and Safari at the time of writing. You may want to do your own feature checks, I recommend using Modernizr .

LINKS & REFERENCES

4 thoughts on “simple voice search using javascript speech recognition”.

Thanks for sharing.

Thanks for sharing your code. It works fine. I’m facing issue while entering number in textbox via microphone voice. extra space is added automatically after every 4 numbers. Eg., Suppose I want to insert ‘1234567894’ in textbox but it gets inserted as ‘1234 5678 94’. How can I remove space between these numbers?

Thanks for the solution.

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Speech Recognition - Run continuously

I'm trying to create an HTML5-powered voice-controlled editor using the Speech Recognition API. Currently, the problem is when you start recording, it only lasts for a certain amount of time (basically until the user stops talking).

I can set continuous and interimResults to true , but that doesn't keep it recording forever. It still ends.

I can also tell it to start again during the end event, but then it asks for permission every time, which is highly disruptive.

Is there a way to allow it to go continuously while only having to ask a user once?

speech-recognition
html5-audio

4 Answers 4

No matter the settings you'll choose, Google Chrome stops the speech recognition engine after a while... there's no way around it.

The only reliable solution I've found for continuous speech recognition, is to start it again by binding to the onend() event, as you've suggested.

If you try a similar technique, be aware of the following:

If you are not on HTTPS, the user will be prompted to give permission over and over again on each restart. For this, and many other reasons, don't compromise on HTTP when using Speech Recognition.

Make sure you are not restarting the speech recognition immediately onend() without some safeguards to make sure you aren't putting the browser into an endless loop (e.g. two open tabs with onend(function() {restart()}) can crash the browser, as I've detailed in this bug report: https://code.google.com/p/chromium/issues/detail?id=296690 ) See https://github.com/TalAter/annyang/blob/1ee294e2b6cb9953adb9dcccf4d3fcc7eca24c2c/src/annyang.js#L214 for how I handle this.

Don't autorestart if the reason for it ending is something like service-not-allowed or not-allowed See https://github.com/TalAter/annyang/blob/1ee294e2b6cb9953adb9dcccf4d3fcc7eca24c2c/src/annyang.js#L196

You can see how I handled this in my code - https://github.com/TalAter/annyang/blob/master/src/annyang.js

@samanime If you believe this is the most accurate answer, please mark the answer as the correct one. – Tal Ater Commented Jun 2, 2015 at 21:14
1 Just an update. The github links seem to be broken. Here is the current link I found. github.com/TalAter/annyang – jkw4703 Commented Aug 9, 2018 at 22:31
All links have been fixed to ones that shouldn't break with future versions of annyang – Tal Ater Commented Aug 15, 2018 at 13:29
1 This answer is great! the "be aware of the following" section is very useful and goes above-and-beyond what the OP was asking – Brian Risk Commented May 30, 2020 at 13:43

Kindly try this code, I think it does what you need:

<!DOCTYPE html> <html> <head> <title>Speech recognition</title> <style> #result{ border: 2px solid black; height: 200px; border-radius: 3px; font-size: 14px; } button{ position: absolute; top: 240px; left: 50%; } </style> <script type="application/javascript"> function start(){ var r = document.getElementById("result"); if("webkitSpeechRecognition" in window){ var speechRecognizer = new webkitSpeechRecognition(); speechRecognizer.continuous = true; speechRecognizer.interimResults = true; speechRecognizer.lang = "en-US"; speechRecognizer.start(); var finalTranscripts = ""; speechRecognizer.onresult = function(event){ var interimTranscripts = ""; for(var i=event.resultIndex; i<event.results.length; i++){ var transcript = event.results[i][0].transcript; transcript.replace("\n", "<br>"); if(event.results[i].isFinal){ finalTranscripts += transcript; } else{ interimTranscripts += transcript; } r.innerHTML = finalTranscripts + '<span style="color: #999;">' + interimTranscripts + '</span>'; } }; speechRecognizer.onerror = function(event){ }; } else{ r.innerHTML = "Your browser does not support that."; } } </script> </head> <body> <div id="result"></div> <button onclick="start()">Listen</button> </body> </html>

I was looking for this "speechRecognizer.continuous = true;" thanks a lot! – SoEzPz Commented Jan 6, 2019 at 3:44

HTML 5 Speech Continuously requires this...

You will have to to be rstarting the engine every few seconds.see at my code, https://github.com/servo-ai/servo-platform/blob/master/editor/src/assets/js/voice/asr.js

Note: after v 70 of chrome, a click UI is needed at least once

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7-Top-Programming-Languages-for-Machine-Learning-1

7 Top Machine Learning Programming Languages

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Whether you realize it or not, you encounter machine learning every day. Every time you fill out a captcha, use Siri, chat with an online customer service rep, or flip through Netflix recommendations, you’re benefitting from machine learning.

Machine Learning Engineers work behind the scenes to create the systems that computers need to operate various software. Interested in becoming a Machine Learning Engineer? First, you’ll need to learn:

What is machine learning?

What are the best programming languages for machine learning, what does a machine learning engineer do.

Machine learning is essentially teaching a computer to make its own predictions. For example, a Machine Learning Engineer might create an algorithm that the computer uses to recognize patterns within data and then decide what the next part of the pattern should be.

Patterns can come in many different settings and can be used for a variety of purposes. Common examples of machine learning include:

Speech recognition: Any application that utilizes speech recognition uses machine learning to identify the words you’re saying and translate them into text the computer will understand.
Social media: Probably the most well-known machine learning application, social media platforms generate ads and suggestions based on your likes and interests.
Virtual assistants: Every time you ask a question or speak to your smart devices, they’re learning your habits and better understanding how to answer you.
Image recognition: You help computers learn the difference between different images each time you’re asked to click the image that’s right side up to verify your identity.
Streaming services: Every time you watch an episode of your favorite show or click on a new movie, the system recognizes your activities and uses the patterns created to recommend similar content.

If you’re considering a career in this field, you’re probably wondering which programming language is best for machine learning. While you have many options, here are 7 of the most popular:

Python is one of the leading programming languages for its simple syntax and readability. Machine learning algorithms can be complicated, but having flexible and easily read code helps engineers create the best solution for the specific problem they’re working on.

Python supports a variety of frameworks and libraries, which allows for more flexibility and creates endless possibilities for an engineer to work with.

Machine Learning Specialists can choose from Python’s many libraries to tackle whatever problems they have in the best and most direct way possible. These libraries vary from artificial intelligence to natural language processing to deep learning . Some of the most popular Python libraries for machine learning include:

sci-kit image
sci-kit learn

If you’re interested in learning one of the most popular and easy-to-learn programming languages, check out our Python courses .

The R programming language focuses primarily on numbers and has a wide range of data sampling, model evaluation, and data visualization techniques. It’s a powerful language — especially if you’re dealing with large volumes of statistical data.

A Machine Learning Engineer can use R to understand statistical data so they can apply those principles to vast amounts of data at once. The solutions it provides can help an engineer streamline data so that it’s not overwhelming.

R comes with its own supply of packages for engineers to utilize to get their work done efficiently, such as:

randomFOREST

3. Java and 4. JavaScript

Java and JavaScript are some of the most widely used and multipurpose programming languages out there. Most websites are created using these languages, so using them in machine learning makes the integration process much simpler.

Both Java and JavaScript are known to be reliable and have the competency to support heavy data processing. Each language also comes with unique machine learning libraries.

Java machine learning libraries:

JavaScript machine learning libraries

TensorFlow.js

To start learning how to use either of these languages, check out the links below:

Java courses
JavaScript courses

C++ is another popular programming language widely used for performance-critical applications that need memory management and speed at the forefront. These features make it an ideal programming language to use when working in machine learning.

C++ is a competent language that can manipulate algorithms and take on memory management at a very detailed level. Moreover, its speed and efficiency enable it to be used to develop well-coded and fast algorithms.

This top favorite has many machine learning and artificial intelligence libraries, such as:

Turi Create

Ready to get started with C++ ? Try Learn C++ .

Shell can be used to develop algorithms, machine learning models, and applications. It uses mathematical models to collect and prepare data. Shell supplies you with an easy and simple way to process data with its powerful, quick, and text-based interface.

Shell is available to use on all operating systems, including macOS, Windows, and Linux. It also comes with libraries that can be utilized in machine learning. These libraries include:

Ml-notebook
Docker-prediction

Go (Golang) is an open-sourced programming language that was created by Google. This intuitive language is used in a variety of applications and is considered one of the fastest-growing programming languages.

Go is capable of working with large data sets by processing multiple tasks together. It has its own built-in vocabulary and is a system-level programming language.

Go also has features like dynamic typing and garbage collection that make it popular with cloud computing services.

Go was designed to make it easier for more people to learn programming. It’s considered one of the easier languages to learn, so you’ll have no problem breaking into machine learning with libraries like:

Now that you’re familiar with some popular machine learning languages, let’s take a moment to explore what exactly your job would entail as a Machine Learning Engineer .

Your job will vary depending on the company you work for and the specific projects you’re involved in. In general, Machine Learning Engineers use their programming skills to create the systems computers learn from.

This involves preparing the needed data, cleaning it, and finding the correct model to use it. This allows the computer to provide the resulting suggestions based on the patterns it identified. The program developed by the Machine Learning Engineer will then continue to process data and learn how to better suggest or answer from the data it collects.

The responsibilities of a Machine Learning Engineer may include:

Maintaining, creating, and streamlining data pipelines
Keeping precise documentation
Working to improve processes and systems

Some Machine Learning Engineers also create algorithms that help their companies learn about their users preferences and offer personalized suggestions based on their interests. This technology is popular with entertainment, shopping, news, and travel platforms, so there’s a high demand for Machine Learning Engineers across these industries.

Want to learn how to create these algorithms yourself? Check out our Build a Recommender System skill path to start from scratch; and if you’ve already got some Python skills, try Learn Recommender Systems .

Which programming language will you choose?

If you’re still asking yourself about the best language to choose from , the answer is that it comes down to the nature of your job. Each language is unique and used for a specific task. Many Machine Learning Engineers have several languages in their tech stacks to diversify their skillset.

Testing, experimenting, and experience will help you know how to best approach each problem when creating the system needed for whatever machine learning application you’re designing. Choose a language that best suits your abilities to start your machine learning career. To get started, check out our catalog of programming courses .

Or if you want to streamline your learning, try our Data Scientist: Machine Learning Specialist and Machine Learning/AI Engineer career paths. Each course offers step-by-step guidance on which skills you should learn, and by the end, you’ll have everything you need to start applying to entry-level positions in machine learning.

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Easy Way to Learn Speech Recognition in Java With a Speech-To-Text API

Rev › Blog › Resources › Other Resources › Speech-to-Text APIs › Easy Way to Learn Speech Recognition in Java With a Speech-To-Text API

Here we explain show how to use a speech-to-text API with two Java examples.

We will be using the Rev AI API ( free for your first 5 hours ) that has two different speech-to-text API’s:

Asynchronous API – For pre-recorded audio or video
Streaming API – For live (streaming) audio or video

Asynchronous Rev AI API Java Code Example

We will use the Rev AI Java SDK located here . We use this short audio , on the exciting topic of HR recruiting.

First, sign up for Rev AI for free and get an access token.

Create a Java project with whatever editor you normally use. Then add this dependency to the Maven pom.xml manifest:

The code sample below is here . We explain it and show the output.

Submit the job from a URL:

Most of the Rev AI options are self-explanatory, for the most part. You can use the callback to kick off downloading the transcription in another program that is on standby, listening on http, if you don’t want to use the polling method we use in this example.

Put the program in a loop and check the job status. Download the transcription when it is done.

The SDK returns captions as well as text.

Here is the complete code:

It responds:

You can get the transcript with Java.

Or go get it later with curl, noting the job id from stdout above.

This returns the transcription in JSON format:

Streaming Rev AI API Java Code Example

A stream is a websocket connection from your video or audio server to the Rev AI audio-to-text entire.

We can emulate this connection by streaming a .raw file from the local hard drive to Rev AI.

One Ubuntu run:

Download the audio then convert it to .raw format as shown below. Converted it from wav to raw with the following ffmpeg command:

As you run that is gives key information about the audio file:

To explain, first we set a websocket connection and start streaming the file:

The important items to set here are the sampling rate (not bit rate) and format. We match this information from ffmpeg: Audio: pcm_f32le, 48000 Hz ,

After the client connects, the onConnected event sends a message. We can get the jobid from there. This will let us download the transcription later if we don’t want to get it in real-time.

To get the transcription in real time, listen for the onHypothesis event:

Here is what the output looks like:

What is the Best Speech Recognition API for Java?

Accuracy is what you want in a speech-to-text API, and Rev AI is a one-of-a-kind speech-to-text API in that regard.

You might ask, “So what? Siri and Alexa already do speech-to-text, and Google has a speech cloud API.”

That’s true. But there’s one game-changing difference:

The data that powers Rev AI is manually collected and carefully edited . Rev pays 50,000 freelancers to transcribe audio & caption videos for its 99% accurate transcription & captioning services . Rev AI is trained with this human-sourced data, and this produces transcripts that are far more accurate than those compiled simply by collecting audio, as Siri and Alexa do.

how to make speech recognition in javascript

Rev AI’s accuracy is also snowballing, in a sense. Rev’s speech recognition system and API is constantly improving its accuracy rates as its dataset grows and the world-class engineers constantly improve the product.

Labelled Data and Machine Learning

Why is human transcription important?

If you are familiar with machine learning then you know that converting audio to text is a classification problem.

To train the computer to transcribe audio ML programmers feed feature-label data into their model. This data is called a training set .

Features (sound) are input and labels (the corresponding letter) are output, calculated by the classification algorithm.

Alexa and Siri vacuum up this data all day long. So you would think they would have the largest and therefore most accurate training data.

But that’s only half of the equation. It takes many hours of manual work to type in the labels that correspond to the audio. In other words, a human must listen to the audio and type the corresponding letter and word.

This is what Rev AI has done.

It’s a business model that has taken off, because it fills a very specific need.

For example, look at closed captioning on YouTube. YouTube can automatically add captions to it’s audio. But it’s not always clear. You will notice that some of what it says is nonsense. It’s just like Google Translate: it works most of the time, but not all of the time.

The giant tech companies use statistical analysis, like the frequency distribution of words, to help their models.

But they are consistently outperformed by manually trained audio-to-voice training models.

More Caption & Subtitle Articles

Everybody’s Favorite Speech-to-Text Blog

We combine AI and a huge community of freelancers to make speech-to-text greatness every day. Wanna hear more about it?

EURASIP Journal on Audio, Speech, and Music Processing

Featured article: "Variational Autoencoders for chord sequence generation conditioned on Western harmonic music complexity"

In recent years, the adoption of deep learning techniques has allowed to obtain major breakthroughs in the automatic music generation research field, sparking a renewed interest in generative music. A great deal of work has focused on the possibility of conditioning the generation process in order to be able to create music according to human-understandable parameters. In this paper, we propose a technique for generating chord progressions conditioned on harmonic complexity, as grounded in the Western music theory. Read the full article here.

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Advanced Signal Processing and Machine Learning for Acoustic Scene Analysis and Signal Enhancement Deadline for submission: 31 May 2024

EURASIP Journal on Audio, Speech, and Music Processing welcomes proposals for Special Issues on timely topics relevant to the field of signal processing. If you are interested in publishing a collection with us, please read our guidelines here.

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EURASIP Journal on Audio, Speech, and Music Processing (JASM) welcomes Special Issues on timely topics related to the field of signal processing. The objective of Special Issues is to bring together recent and high quality works in a research domain, to promote key advances in theory and applications of the processing of various audio signals, with a specific focus on speech and music and to provide overviews of the state-of-the-art in emerging domains.

Special issue proposals in the format of a single PDF document , are required to be submitted by e-mail to [email protected] . Please include in the subject line ‘JASM Special Issue Proposal’.

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Gender-driven english speech emotion recognition with genetic algorithm, 1. introduction.

Propose a novel speech gender–emotion recognition model.
Extract various features from speech for gender and emotion recognition.
Utilize a genetic algorithm for high-dimensional feature selection for fast emotion recognition, in which the algorithm is improved through feature evaluation, the selection of parents, crossover, and mutation.
Validate the performance of the proposed algorithm on four English datasets.

2. Related Works

3. materials and methods, 3.1. emotional databases, 3.2. feature extraction, 3.3. improved genetic algorithm, 3.3.1. feature evaluation, 3.3.2. the selection of parents.

The selection of parents

3.3.3. Crossover and Mutation

Mutation

4. Experimental Results and Analysis

4.1. objective function, 4.2. experimental analysis, 4.3. discussion, 5. conclusions, author contributions, institutional review board statement, data availability statement, conflicts of interest.

Bhushan, B. Optimal Feature Learning for Speech Emotion Recognition—A DeepNet Approach. In Proceedings of the 2023 International Conference on Data Science and Network Security (ICDSNS), Tiptur, India, 28–29 July 2023; IEEE: New York, NY, USA, 2023; pp. 1–6. [ Google Scholar ]
Wani, T.M.; Gunawan, T.S.; Qadri, S.A.A.; Kartiwi, M.; Ambikairajah, E. A comprehensive review of speech emotion recognition systems. IEEE Access 2021 , 9 , 47795–47814. [ Google Scholar ] [ CrossRef ]
Donuk, K. CREMA-D: Improving Accuracy with BPSO-Based Feature Selection for Emotion Recognition Using Speech. J. Soft Comput. Artif. Intell. 2022 , 3 , 51–57. [ Google Scholar ] [ CrossRef ]
Fahad, M.S.; Ranjan, A.; Yadav, J.; Deepak, A. A survey of speech emotion recognition in natural environment. Digit. Signal Process. 2021 , 110 , 102951. [ Google Scholar ] [ CrossRef ]
Akçay, M.B.; Oğuz, K. Speech emotion recognition: Emotional models, databases, features, preprocessing methods, supporting modalities, and classifiers. Speech Commun. 2020 , 116 , 56–76. [ Google Scholar ] [ CrossRef ]
Issa, D.; Demirci, M.F.; Yazici, A. Speech emotion recognition with deep convolutional neural networks. Biomed. Signal Process. Control 2020 , 59 , 101894. [ Google Scholar ] [ CrossRef ]
Hu, G.; Zhong, J.; Wang, X.; Wei, G. Multi-strategy assisted chaotic coot-inspired optimization algorithm for medical feature selection: A cervical cancer behavior risk study. Comput. Biol. Med. 2022 , 151 , 106239. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Barrera-García, J.; Cisternas-Caneo, F.; Crawford, B.; Gómez Sánchez, M.; Soto, R. Feature Selection Problem and Metaheuristics: A Systematic Literature Review about Its Formulation, Evaluation and Applications. Biomimetics 2023 , 9 , 9. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Hu, P.; Pan, J.S.; Chu, S.C.; Sun, C. Multi-surrogate assisted binary particle swarm optimization algorithm and its application for feature selection. Appl. Soft Comput. 2022 , 121 , 108736. [ Google Scholar ] [ CrossRef ]
Jia, H.; Rao, H.; Wen, C.; Mirjalili, S. Crayfish optimization algorithm. Artif. Intell. Rev. 2023 , 56 , 1919–1979. [ Google Scholar ] [ CrossRef ]
Jia, H.; Peng, X.; Lang, C. Remora optimization algorithm. Expert Syst. Appl. 2021 , 185 , 115665. [ Google Scholar ] [ CrossRef ]
Hu, G.; Zhong, J.; Zhao, C.; Wei, G.; Chang, C.T. LCAHA: A hybrid artificial hummingbird algorithm with multi-strategy for engineering applications. Comput. Methods Appl. Mech. Eng. 2023 , 415 , 116238. [ Google Scholar ] [ CrossRef ]
Zhao, W.; Wang, L.; Zhang, Z.; Fan, H.; Zhang, J.; Mirjalili, S.; Khodadadi, N.; Cao, Q. Electric eel foraging optimization: A new bio-inspired optimizer for engineering applications. Expert Syst. Appl. 2024 , 238 , 122200. [ Google Scholar ] [ CrossRef ]
Wu, D.; Jia, H.; Abualigah, L.; Xing, Z.; Zheng, R.; Wang, H.; Altalhi, M. Enhance teaching-learning-based optimization for tsallis-entropy-based feature selection classification approach. Processes 2022 , 10 , 360. [ Google Scholar ] [ CrossRef ]
Lu, J.; Su, X.; Zhong, J.; Hu, G. Multi-objective shape optimization of developable Bézier-like surfaces using non-dominated sorting genetic algorithm. Mech. Ind. 2023 , 24 , 38. [ Google Scholar ] [ CrossRef ]
Gao, Y.; Gao, L.; Liu, Y.; Wu, M.; Zhang, Z. Assessment of water resources carrying capacity using chaotic particle swarm genetic algorithm. J. Am. Water Resour. Assoc. 2024 , 60 , 667–686. [ Google Scholar ] [ CrossRef ]
Pan, J.S.; Hu, P.; Snášel, V.; Chu, S.C. A survey on binary metaheuristic algorithms and their engineering applications. Artif. Intell. Rev. 2022 , 56 , 6101–6167. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Yue, L.; Hu, P.; Chu, S.C.; Pan, J.S. Genetic Algorithm for High-Dimensional Emotion Recognition from Speech Signals. Electronics 2023 , 12 , 4779. [ Google Scholar ] [ CrossRef ]
Zhou, J.; Hua, Z. A correlation guided genetic algorithm and its application to feature selection. Appl. Soft Comput. 2022 , 123 , 108964. [ Google Scholar ] [ CrossRef ]
Song, H.; Wang, J.; Song, L.; Zhang, H.; Bei, J.; Ni, J.; Ye, B. Improvement and application of hybrid real-coded genetic algorithm. Appl. Intell. 2022 , 52 , 17410–17448. [ Google Scholar ] [ CrossRef ]
Li, J.; Li, L. A hybrid genetic algorithm based on information entropy and game theory. IEEE Access 2020 , 8 , 36602–36611. [ Google Scholar ]
Yan, C.; Li, M.X.; Liu, W. Application of Improved Genetic Algorithm in Function Optimization. J. Inf. Sci. Eng. 2019 , 35 , 1299. [ Google Scholar ]
Harifi, S.; Mohamaddoust, R. Zigzag mutation: A new mutation operator to improve the genetic algorithm. Multimed. Tools Appl. 2023 , 82 , 1–22. [ Google Scholar ] [ CrossRef ]
Dorea, C.C.; Guerra, J.A., Jr.; Morgado, R.; Pereira, A.G. Multistage markov chain modeling of the genetic algorithm and convergence results. Numer. Funct. Anal. Optim. 2010 , 31 , 164–171. [ Google Scholar ] [ CrossRef ]
Li, J.-H.; Li, M. An analysis on convergence and convergence rate estimate of elitist genetic algorithms in noisy environments. Optik 2013 , 124 , 6780–6785. [ Google Scholar ]
Peng, Y.; Luo, X.; Wei, W. A new fuzzy adaptive simulated annealing genetic algorithm and its convergence analysis and convergence rate estimation. Int. J. Control Autom. Syst. 2014 , 12 , 670–679. [ Google Scholar ] [ CrossRef ]
Bisio, I.; Delfino, A.; Lavagetto, F.; Marchese, M.; Sciarrone, A. Gender-driven emotion recognition through speech signals for ambient intelligence applications. IEEE Trans. Emerg. Top. Comput. 2013 , 1 , 244–257. [ Google Scholar ] [ CrossRef ]
Bhattacharya, P.; Gupta, R.K.; Yang, Y. Exploring the contextual factors affecting multimodal emotion recognition in videos. IEEE Trans. Affect. Comput. 2021 , 14 , 1547–1557. [ Google Scholar ] [ CrossRef ]
Zaman, S.R.; Sadekeen, D.; Alfaz, M.A.; Shahriyar, R. One source to detect them all: Gender, age, and emotion detection from voice. In Proceedings of the 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC), Madrid, Spain, 12–16 July 2021; IEEE: New York, NY, USA, 2021; pp. 338–343. [ Google Scholar ]
Verma, D.; Mukhopadhyay, D.; Mark, E. Role of gender influence in vocal Hindi conversations: A study on speech emotion recognition. In Proceedings of the 2016 International Conference on Computing Communication Control and Automation (ICCUBEA), Pune, India, 12–13 August 2016; IEEE: New York, NY, USA, 2016; pp. 1–6. [ Google Scholar ]
Bandela, S.R.; Siva Priyanka, S.; Sunil Kumar, K.; Vijay Bhaskar Reddy, Y.; Berhanu, A.A. Stressed Speech Emotion Recognition Using Teager Energy and Spectral Feature Fusion with Feature Optimization. Comput. Intell. Neurosci. 2023 , 2023 , 5765760. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Rituerto-González, E.; Mínguez-Sánchez, A.; Gallardo-Antolín, A.; Peláez-Moreno, C. Data augmentation for speaker identification under stress conditions to combat gender-based violence. Appl. Sci. 2019 , 9 , 2298. [ Google Scholar ] [ CrossRef ]
Kaggle. Speech Emotion Recognition for Emergency Calls. Available online: https://www.kaggle.com/datasets/anuvagoyal/speech-emotion-recognition-for-emergency-calls (accessed on 12 June 2024).
Busso, C.; Bulut, M.; Lee, C.C.; Kazemzadeh, A.; Mower, E.; Kim, S.; Chang, J.N.; Lee, S.; Narayanan, S.S. IEMOCAP: Interactive emotional dyadic motion capture database. Lang. Resour. Eval. 2008 , 42 , 335–359. [ Google Scholar ] [ CrossRef ]
Bajaj, A.; Jha, A.; Vashisth, L.; Tripathi, K. Comparative Wavelet and MFCC Speech Emotion Recognition Experiments on the RAVDESS Dataset. Math. Stat. Eng. Appl. 2022 , 71 , 1288–1293. [ Google Scholar ]
Mengash, H.A.; Alruwais, N.; Kouki, F.; Singla, C.; Abd Elhameed, E.S.; Mahmud, A. Archimedes Optimization Algorithm-Based Feature Selection with Hybrid Deep-Learning-Based Churn Prediction in Telecom Industries. Biomimetics 2023 , 9 , 1. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Yao, L.; Yang, J.; Yuan, P.; Li, G.; Lu, Y.; Zhang, T. Multi-Strategy Improved Sand Cat Swarm Optimization: Global Optimization and Feature Selection. Biomimetics 2023 , 8 , 492. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Sun, L.; Li, Q.; Fu, S.; Li, P. Speech emotion recognition based on genetic algorithm–decision tree fusion of deep and acoustic features. ETRI J. 2022 , 44 , 462–475. [ Google Scholar ] [ CrossRef ]
Yogesh, C.; Hariharan, M.; Ngadiran, R.; Adom, A.H.; Yaacob, S.; Polat, K. Hybrid BBO_PSO and higher order spectral features for emotion and stress recognition from natural speech. Appl. Soft Comput. 2017 , 56 , 217–232. [ Google Scholar ]
Garain, A.; Ray, B.; Giampaolo, F.; Velasquez, J.D.; Singh, P.K.; Sarkar, R. GRaNN: Feature selection with golden ratio-aided neural network for emotion, gender and speaker identification from voice signals. Neural Comput. Appl. 2022 , 34 , 14463–14486. [ Google Scholar ] [ CrossRef ]

Category	Description	Features
Gender	Pitch	max, min, median, mean, variance and derivatives
Emotion	PCM loudness	max, min, median, mean, variance and derivatives
	MFCC [0–14]	max, min, median, mean, variance, derivatives, and their corresponding first-order delta coefficients (FDE) of smooth low-level descriptors
	log Mel Freq. Band [0–7]	skewness, kurtosis, max, min, median, mean, variance, derivatives, and FDE
	LSP Frequency [0–7]	max, min, median, mean, variance, derivatives, and FDE
	F0 by Sub-Harmonic Sum	lin. regression error Q/A-, max, min, median, mean, variance, derivatives, and FDE
	F0 Envelope quartile	quartile—1/2/3, max, min, median, mean, variance, derivatives, and FDE
	Voicing Probability	quartile range—2-1/3-2/3-1, max, min, median, mean, variance, derivatives, and FDE
	Jitter local	percentile 1/99, max, min, median, mean, variance, derivatives, and FDE
	Jitter DDP	percentile range 99-1, max, min, median, mean, variance, derivatives, and FDE
	Shimmer local	up-level time—75/90, max, min, median, mean, variance, derivatives, and FDE

Algorithms	Main Parameters
GA	pC = 1; mu = 0.02;
IGA	mu = 0.02;
BBO_PSO	pMutation = 0.1; KeepRate = 0.2;
MA	mu = 0.01; DANCE = 5; fl = 1;

Datasets	MA	BBO_PSO	GA	IGA
CREMA-D	0.6890	0.6181	0.5923	0.6569
EmergencyCalls	0.6703	0.6077	0.6400	0.7471
IEMOCAP-S1	0.5671	0.4819	0.4928	0.6023
RAVDESS	0.6821	0.6532	0.5852	0.6838
>/≈/<	1/1/2	0/0/4	0/0/4	3/0/0
Rank	1.75	3.75	3.25	1.25
p-Value	0.0169

Dataset	MA		BBO_PSO		GA		IGA
Dataset	Length	Time	Length	Time	Length	Time	Length	Time
CREMA-D	317.4	40,543.1062	253.6	48,106.5402	461.1	20,755.5475	197.2	12,860.7447
EmergencyCalls	318.4	1433.4570	240.8	932.8905	482.65	706.4227	197.65	577.1138
IEMOCAP-S1	318.35	9930.3462	243.65	9985.9357	485.9	5127.9112	188.75	3476.7207
RAVDESS	319.95	8491.6366	245.45	6492.9197	492.3	4143.9636	193.5	2612.5911

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Share and Cite

Yue, L.; Hu, P.; Zhu, J. Gender-Driven English Speech Emotion Recognition with Genetic Algorithm. Biomimetics 2024 , 9 , 360. https://doi.org/10.3390/biomimetics9060360

Yue L, Hu P, Zhu J. Gender-Driven English Speech Emotion Recognition with Genetic Algorithm. Biomimetics . 2024; 9(6):360. https://doi.org/10.3390/biomimetics9060360

Yue, Liya, Pei Hu, and Jiulong Zhu. 2024. "Gender-Driven English Speech Emotion Recognition with Genetic Algorithm" Biomimetics 9, no. 6: 360. https://doi.org/10.3390/biomimetics9060360

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Posted on Aug 22, 2022 • Updated on Aug 25, 2022

Speech Recognition with JavaScript

Cover image credits: dribbble

Some time ago, speech recognition API was added to the specs and we got partial support on Chrome, Safari, Baidu, android webview, iOS safari, samsung internet and Kaios browsers ( see browser support in detail ).

Disclaimer: This implementation won't work in Opera (as it doesn't support the constructor) and also won't work in FireFox (because it doesn't support a single thing of it) so if you're using one of those, I suggest you to use Chrome -or any other compatible browser- if you want to take a try.

Speech recognition code and PoC

Edit: I realised that for any reason it won't work when embedded so here's the link to open it directly .

The implementation I made currently supports English and Spanish just to showcase.

Quick instructions and feature overview:

Choose one of the languages from the drop down.
Hit the mic icon and it will start recording (you'll notice a weird animation).
Once you finish a sentence it will write it down in the box.
When you want it to stop recording, simply press the mic again (animation stops).
You can also hit the box to copy the text in your clipboard.

Speech Recognition in the Browser with JavaScript - key code blocks:

This implementation currently supports the following languages for speech recognition:

If you want me to add support for more languages tell me in the comment sections and I'm updating it in a blink so you can test it on your own language 😁

That's all for today, hope you enjoyed I sure did doing that

Top comments (20)

Templates let you quickly answer FAQs or store snippets for re-use.

Location 3000
Work Mr at StartUp
Joined Aug 17, 2019

It's cool mate. Very good

Location Spain
Education Higher Level Education Certificate on Web Application Development
Work Tech Lead/Lead Dev
Joined Apr 19, 2019

Thank you! 🤖

Can u add Telugu a Indian language:)

I can try, do you know the IETF/ISO language code for it? 😁

Location İstanbul, Turkey
Joined Apr 28, 2022

This is really awesome. Could you please add the Turkish language? I would definitely like to try this in my native language and use it in my projects.

Location Cyprus
Work CTO at AINIRO AS
Joined Mar 13, 2022

Cool. I once created a speech based speech recognition thing based upon MySQL and SoundEx allowing me to create code by speaking through my headphones. It was based upon creating a hierarchical “menu” where I could say “Create button”. Then the machine would respond with “what button”, etc. The thing of course produced Hyperlambda though. I doubt it can be done without meta programming.

One thing that bothers me is that this was 5 years ago, and speech support has basically stood 100% perfectly still in all browsers since then … 😕

Not in all of them, (e.g. Opera mini, FireFox mobile), it's a nice to have in browsers, specially targeting accessibility, but screen readers for blind people do the job and, on the other hand, most implementations for any other purpose send data to a backend using streams so they can process the incoming speech plus use the user feedback to train an IA among others and without hurting the performance.

...allowing me to create code by speaking through my headphones... ... I doubt it can be done without meta programming.

I agree on this. The concept "metaprogramming" is extense and covers different ways in which it can work (or be implemented) and from its own definition it is a building block for this kind of applications.

Location Rio de Janeiro, RJ
Education Master Degree
Work FullStack and Mobile Developer
Joined May 18, 2021

Thank you 🙏. I'd like that you put in Brazilian Portuguse too.

Added both Portugal and Brazilian portuguese 😁

Work Student
Joined Jul 21, 2022

Thanks you 🙏. I'd like that you put in french too.

Thank you! 😁

Work Technical Manager @ Gabrieli Media Group
Joined Aug 29, 2022

Thank you very much for your useful article and implementation. Does it support Greek? Have a nice (programming) day

Hi Symeon, added support for Greek el-GR , try it out! 😃

Education Cameroon
Joined Aug 26, 2022

I added support for some extra languages in the mean time 😁

Joined Jan 15, 2023

Can you please add urdu language

Hi @aheedkhan I'm not maintaining this anymore but feel free to fork the pen! 😄

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New UBC engineering research facility accelerates innovation in BC’s hydrogen energy sector

Car and cyclist passing UBC's Smart Hydrogen Energy District

BC’s hydrogen infrastructure enters a new era with today’s launch of the $23-million Smart Hydrogen Energy District (SHED) at UBC. Equipped with a hydrogen fueling station, this facility is expected to pave the way for breakthroughs in critical energy research.

SHED will produce hydrogen using solar and hydro power to operate a water electrolyser, making the process completely green and renewable. It is one of the first initiatives to combine hydro, solar and hydrogen energy at a single site, connecting these renewable energy sources to a unified micro-grid. SHED will be the province's first hydrogen station to serve light- and heavy-duty vehicles.

The Honourable Josie Osborne, Minister of Energy, Mines and Low Carbon Innovation, attended the opening today at UBC’s Vancouver campus.

“The UBC Smart Hydrogen Energy District (SHED) is yet another leap forward in building a clean economy and creating new opportunities for British Columbians,” said Minister Osborne. “By integrating energy, transportation, and design, SHED not only supports our CleanBC goals but it also positions British Columbia as a world leader in the hydrogen economy. Projects like this demonstrate our commitment to producing clean energy and ensuring a prosperous future for generations to come.”

“We are grateful to the provincial and federal governments, private sector partners and others for their critical investment in this research facility, which further strengthens UBC’s position as a global leader in climate solutions and energy systems innovation,” said UBC President and Vice-Chancellor Dr. Benoit-Antoine Bacon. “This new space gives UBC scholars significant new research and learning opportunities that will help shape our society and economy in the years ahead.”

Producing clean energy locally

“Hydrogen can play a critical role in Canada’s transition to a low-carbon economy,” said Dr. Walter Mérida, SHED research lead and professor of mechanical engineering in the Faculty of Applied Science.

“With SHED, we demonstrate hydrogen as a bridge between renewable electricity and sustainable energy services. As technologies become smart and interconnected, we can stop thinking of gas, electrical and digital networks as separate entities.”

Dr. Walter Mérida presents a video outlining the features of SHED.

SHED combines various technologies within a city block, serving as a model for compact urban planning. A rooftop solar array powers both the hydrogen fueling station and nearby electric vehicle charging stations. Two-way charging will enable parked EVs to both draw power from the grid and give excess stored electricity back to the grid during peak hours when there is extra energy demand.

“Cars sit in parking spaces most of the time—with the right infrastructure, they can also serve as mass power banks, stabilizing the electric grids of the future,” said Mérida.

A secure 5G network connects SHED’s different systems, enabling researchers to create digital simulations for energy, transportation and urban planning research.

Powering vital collaborations

The global hydrogen market is expected to grow significantly in the coming decades, and Canada will need sustained research to maintain and expand its leadership in hydrogen technologies, said Mérida.

“The first UBC spinoff company from this work has launched. With interest in hydrogen booming across the country, we hope SHED attracts other clean-energy innovators. Our goal is to accelerate climate solutions through insights from this project and seek industry and private sector partners for collaboration.”

SHED received generous funding from the following partners:

Ministry of Energy, Mines and Low Carbon Innovation – $8.3 million in low-carbon fuel standard credits
Government of Canada – $5 million
Canada Foundation for Innovation – $4.6 million
British Columbia Knowledge Development Fund – $4.6 million
$800,000 from industry partners, including HTEC

“UBC’s tradition of nurturing innovators continues today as we mark the grand opening of the Smart Hydrogen Energy District,” said The Honourable Harjit S. Sajjan, Minister of Emergency Preparedness and Minister responsible for the Pacific Economic Development Agency of Canada (PacifiCan). “This is one example of the ground-breaking work taking place across our province that is propelling us towards a net-zero future. With support from the Government of Canada, home-grown innovation is fueling economic growth for British Columbians today and for years to come.”

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SZA, Steely Dan, R.E.M., Trey Anastasio, Carrie Underwood and Many More Light up 2024 Songwriters Hall of Fame Ceremony

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NEW YORK, NEW YORK - JUNE 13: SZA and Nile Rodgers speak onstage during the 2024 Songwriters Hall of Fame Induction and Awards Gala at New York Marriott Marquis Hotel on June 13, 2024 in New York City. (Photo by Bennett Raglin/Getty Images for Songwriters Hall Of Fame)

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On this night, one can see Lady Gaga singing Four Non-Blondes’ hit “What’s Up” to Linda Perry; Stevie Nicks belting “The Rose” to Bette Midler; Emmylou Harris performing Eric Clapton’s heartbreaking hit “Tears in Heaven” for the song’s co-writer Will Jennings; Joe Walsh performing ELO’s “Don’t Bring Me Down” (and saying, “I always wanted to be in ELO — now I have”), and in 2011, the evening ended with Billy Joel and Garth Brooks duetting at the piano in matching Stetson hats.

Every year, honorees who have won multiple Grammy and other awards say this award means the most to them, because a recognition from their peers of the art and craft that is the very foundation of all music: songwriting, a message that is more important than ever as the industry continues to find new and brazen ways to avoid paying the creators of that foundation .

This event is probably the only one on earth that could feature performances from R.E.M., SZA (pictured above with hit producer and SHOF president Nile Rodgers), Carrie Underwood, Andra Day, Phish’s Trey Anastasio, Keith Urban, El Debarge and Jason Isbell, but a similar statement could be made every year.

However, a couple of things were very different this year. For one, the tightly-run show — which often approaches (and sometimes even passes) the five-hour mark due to packed lineups and speeches that can hit the double-digit-minute mark — was done before 11 p.m. for the first time in anyone’s memory. And second but far more significant, longtime SHOF CEO Linda Moran, who was appointed to the role in 2001 and whose industry career reaches back to the 1960s, wasn’t there, for the only reason that could have kept her away: At the top of the show, Board member Evan Lamberg of Universal Music Publishing gently told the audience that Moran wasn’t there because she’s battling leukemia. Yet he quickly countered the gasps in the room by saying that she’s receiving the best possible care and treatment is moving in a good direction. He then led the crowd in a quick video greeting to her before moving on to the show.

The evening’s music kicked off in characteristically far-reaching fashion with the tribute to songwriter Dean Pitchford, as the high school-aged winners of the Hall’s 2024 Abe Olman Scholarship sang his hit for Irene Cara from the film “Fame,” followed by R&B singer Deniece Williams delivering a stellar version of “Let’s Hear It for the Boy,” followed by Kevin Bacon, with his brother Michael on guitar, singing “Footloose,” complete with some fleet footwork from Kevin, who starred in the film some 40 years ago. Pitchford delivered a gracious acceptance speech before singing a medley of his other songs, finishing with “Once Before I Go.”

A dramatic musical shift followed as Phish singer-guitarist Trey Anastasio took the stage to honor Steely Dan — Donald Fagen and the late Walter Becker — playing a sleek medley of “Kid Charlamagne” and “Reeling in the Years,” remarkably channeling Fagen’s voice on the former and showing some dazzling guitar work on both.

Veteran power manager Irving Azoff took the stage to induct his longtime clients, telling an amusing story about how the group, which stubbornly refused to tour during their 1970s commercial peak, asked him one day to schedule a concert. Azoff excitedly booked a show, which quickly sold out, and then asked the group when he could follow with more dates. “‘Oh, we have no intention of touring,’ he recalled them saying. ‘We just wanted to see how big we are,’” and promptly canceled the date. Fagen followed with a brief and gracious thank you.

In a characteristically effusive acceptance speech, SZA noted that her parents were in the audience and said, “Out of all the awards, I feel like this means the most — it validates my entire career.” Accompanied by a guitarist, she then delivered an acoustic version of her 2023 hit single, “Snooze.”

Next up was Carrie Underwood, who used every bit of her formidable vocal power to honor songwriter Hillary Lindsey, writer of one of her biggest hits, “Jesus Take the Wheel.” Lindsey — no mean singer herself — gave a warm acceptance speech before picking up a vintage Gibson acoustic guitar to deliver a medley of two of her other hits, inviting Keith Urban to the stage to duet with her on his Lindsey-cowritten 2016 hit, “Blue Ain’t Your Color.”

The crowd roared as Missy Elliott took the stage to induct her longtime friend and collaborator, hit producer Timbaland (Tomothy Mosely) — the pair, who met as high school students in Virginia, soared into the public consciousness in 1996 by cowriting and coproducing Aaliyah’s “One in a Million” album and haven’t dipped since. She recalled seeing his “big hands on this little keyboard, and I was amazed that he could make songs with [the keyboard’s] weird dog and cat sounds and handclap noises.” She also recalled Moseley’s father, a long-haul truck driver, telling the pair to stop making so much noise “with your boobiddy bop-bop” because he had to rest up for a drive.

“That boobiddy bop-bop is now in the Songwriters Hall of Fame,” she concluded with a laugh.

Moseley gave the evening’s only long acceptance speech before leading the ace house band through a fast-paced, mostly instrumental medley of around a dozen of his hits — complete with a conductor’s wand — including “Big Pimpin’,” “Pony,” “Get Your Freak On,” “Drunk in Love,” “Promiscuous,” and “Suit & Tie,” concluding with Justin Timberlake’s 2006 smash “SexyBack.”

Country star Jason Isbell then took the stage to honor R.E.M. — singer Michael Stipe, guitarist Peter Buck, bassist Mike Mills and drummer Bill Berry — with a rapid-fire version of their 1987 hit “It’s the End of the World as We Know It.” Calling them “my friends and my heroes,” he spoke of their vast influence on him and many others as a young musician. He presented all four members with their trophies and then stepped aside as Stipe gave a heartfelt acceptance speech on behalf of the entire group, which then moved center stage to perform their 1991 hit “Losing My Religion.” (Read Variety ’s full recap of R.E.M.’s speech and performance here .)

View this post on Instagram A post shared by Jem Aswad (@jemaswad)

Warren grew emotional during her characteristically humorous and idiosyncratic speech, thanking her mother “for being the first of many I proved wrong” but then tearing up as she thought of her watching from heaven, her father “for being the first of many I proved right,” Clive Davis, who she called one of her greatest champions, and all of the artists “who make my songs sound a hell of a lot better than I do.”

The evening concluded with El Debarge taking the stage for a show-closing version of Warren’s hit “Rhythm of the Night” — which the audience, pleasantly surprised by the early hour, slowly filtered out into.

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President Lula's speech during the extraordinary session of the Arab League, in Cairo (Egypt)

It is a pleasure to be back at the League of Arab States seat after 20 years.

I want to thank the Secretary-General and everyone present for the valuable opportunity to speak on behalf of Brazil.

We are very proud of the historical and cultural ties that bind us to the Arab world.

We acknowledge and appreciate your invaluable contribution to our country and the progress of humanity.

Brazil was the first Latin American country to receive observer status in this organization.

I had the honor of being the first Brazilian Head of State to occupy this podium in 2003.

The Arab League's commitment to promoting stability and development makes this organization a voice to be closely listened to on major issues of our time.

We are reclaiming the universalist vocation of our foreign policy. We aim to revive and deepen our partnerships with the Global South, with whom we share numerous perspectives, values, challenges, and expectations.

My visits today to Egypt and the Arab League add to those I made to the United Arab Emirates, Saudi Arabia, and Qatar.

They reflect our desire to resume dialogue and collaboration. We maintain resident diplomatic representations in 18 of the 22 countries that make up the Arab League.

We aim to build on the legacy of the Summits between South America and Arab Countries.

There is immense potential in sectors such as trade, investments, environment, science and technology, culture, and development cooperation.

The strength of the relationship between Brazil and the countries of the League is evident in our commercial dynamism.

The increase in trade, which in 2003 was of US$5.4 billion and has grown to US$30 billion in 2023, brings us satisfaction and optimism.

In the current Brazilian Presidency of the G20, we are prioritizing social inclusion and combating hunger and poverty; promoting sustainable development and energy transition; and reforming global governance institutions.

In 2025, we will host COP-30 on climate change in Brazil.

I look forward to the active participation of the Arab League countries in Belém, in the heart of the Amazon, for this crucial discussion for the future of the planet.

Next year, we will also host the BRICS Summit, which now includes the participation of three members from the League: Egypt, Saudi Arabia and the United Arab Emirates.

With the strengthening of the New Development Bank (NDB) through the inclusion of new members, we will continue working to ensure that BRICS remains a positive force in a multipolar world.

Ladies and gentlemen,

I return to Cairo in the context of the terrible humanitarian catastrophe in the Gaza Strip.

In my last visit, the Arab League had presented the Arab Peace Initiative, which represented a balanced and realistic option for resolving the conflict between Israel and Palestine.

Unfortunately, like other initiatives before it, the League's efforts were in vain.

The Hamas attack on October 7 against Israeli civilians is indefensible and has received strong condemnation from Brazil.

The disproportionate and indiscriminate reaction from Israel is unacceptable and constitutes one of the most tragic episodes in this long conflict.

The human and material losses are irreparable.

We cannot trivialize the deaths of thousands of civilians as mere collateral damage. In Gaza, there are almost 30,000 fatal victims, mostly children, the elderly, and women. 80% of the population was forced to leave their homes.

Before our eyes, the population of Gaza is suffering from hunger, thirst, diseases, and other deprivations, as warned by the World Health Organization. The situation in the West Bank, already critical, is also becoming unsustainable.

At a time when the Palestinian people need support the most, wealthy countries decide to cut humanitarian aid to the UN Relief and Works Agency for Palestine Refugees (UNRWA).

Recent allegations against agency officials need proper investigation but should not paralyze it.

Palestinian refugees in Jordan, Syria, and Lebanon will also be left without support.

It is essential to put an end to this inhumanity and cowardice.

Enough of collective punishment.

My government will make a new financial contribution to UNRWA. We urge all countries to maintain and strengthen their contributions.

The most urgent task is to establish a permanent ceasefire that allows for sustainable and unimpeded humanitarian aid and the immediate and unconditional release of hostages.

The persistence of the conflict in Palestine extends far beyond the Middle East. Its effects can lead to unpredictable and catastrophic scenarios.

We proposed and defended resolutions in the Security Council during our presidency in October.

We support the process initiated in the International Court of Justice by South Africa regarding the application of the Convention on the Prevention and Punishment of the Crime of Genocide.

Ground operations in the already overcrowded Rafah region foreshadow new calamities and contradict the spirit of the Court's provisional measures.

It is urgent to halt the killing.

Brazil's position is clear.

There will be no peace until there is a Palestinian state, within mutually agreed and internationally recognized borders, including the Gaza Strip and the West Bank, with East Jerusalem as its capital.

The decision on the existence of an independent Palestinian state was made 75 years ago by the United Nations.

There are no more excuses to prevent Palestine's entry into the UN as a full member. The resumption of peace negotiations is a universal cause.

And it is our cause.

Therefore, I want to renew my wishes for peace and prosperity to all of you.

I would like to conclude by stating that Brazil will continue, in the coming years, to advocate for the recognition of the Palestinian State as a sovereign state, not only by the UN but also on the ground, so that Palestinians can build their lives in peace and with the respect of the rest of the world.

I want to express my gratitude to the Arab League and emphasize the importance you have in drawing humanity's attention to this matter. Mr. Secretary, we need to engage in a crucial debate to reconsider the United Nations and reshape global governance. It is not acceptable for the UN to be governed solely by countries that emerged as victors or losers in World War II.

It is important to remember that the world has changed; geopolitics have evolved. Countries have become more significant. There is no explanation for the fact that the African continent is not represented at the United Nations [Security Council], when it could have two, three representatives. It makes no sense for South America and Latin America to lack representation. It is senseless for a country like India or Germany to be excluded.

In other words, we need to reconsider increasing the number of countries on the Security Council. We must contemplate eliminating the veto power. And it is crucial to recognize that if the UN does not take the existence of its Permanent Security Council seriously, the world will not have peace. Because it is the members of the Permanent Council, the countries that produce and sell weapons, that have been driving recent wars.

This is what happened in Iraq, this is what happened in Libya, you know. Russia did not seek anyone's approval to invade Ukraine. In essence, the UN is severely weakened when it comes to making decisions for Israel to comply with resolutions made over the years.

Therefore, I am here to express my unwavering commitment to continue fighting for peace. Peace is the only possibility we have to build development and improve the lives of the people. Secondly, I want to convey my solidarity to the Palestinian people because, for many years, I have advocated for the necessity of the Palestinian people to have their free and sovereign territory.

And I am here to reaffirm to the Arab countries that, just as we are against Hamas, we are against Israel's behavior, and we are against war. Brazil is a country that has no disputes with any nation worldwide, and we believe that only with the end of war can we build the world of peace we have been dreaming of. Thank you all, and may peace be with us.

COMMENTS

SpeechRecognition
SpeechRecognition. The SpeechRecognition interface of the Web Speech API is the controller interface for the recognition service; this also handles the SpeechRecognitionEvent sent from the recognition service. Note: On some browsers, like Chrome, using Speech Recognition on a web page involves a server-based recognition engine.
JavaScript Speech Recognition Example (Speech to Text)
With the Web Speech API, we can recognize speech using JavaScript. It is super easy to recognize speech in a browser using JavaScript and then getting the text from the speech to use as user input. We have already covered How to convert Text to Speech in Javascript. But the support for this API is limited to the Chrome browser only. So if you ...
Using the Web Speech API
Speech recognition involves receiving speech through a device's microphone, which is then checked by a speech recognition service against a list of grammar (basically, the vocabulary you want to have recognized in a particular app.) When a word or phrase is successfully recognized, it is returned as a result (or list of results) as a text string, and further actions can be initiated as a result.
Web Speech API
The Web Speech API makes web apps able to handle voice data. There are two components to this API: Speech recognition is accessed via the SpeechRecognition interface, which provides the ability to recognize voice context from an audio input (normally via the device's default speech recognition service) and respond appropriately.
Perform Speech Recognition in Your JavaScript Applications
Annyang is a JavaScript Speech Recognition library to control the Website with voice commands. It is built on top of SpeechRecognition Web APIs. In next section, we are going to give an example on how annyang works. 2. artyom.js. artyom.js is a JavaScript Speech Recognition and Speech Synthesis library. It is built on top of Web speech APIs.
Speech Recognition in JavaScript Tutorial
However, Speech Recognition can also include technologies such as Wake Word Detection, Voice Command Recognition, and Voice Activity Detection (VAD). This article provides a thorough guide on integrating on-device Speech Recognition into JavaScript Web apps. We will be learning about the following technologies:
JavaScript Text-to-Speech
Step 1 - Setting Up The App. First, we set up a very basic application using a simple HTML file called index.html and a JavaScript file called script.js . We'll also use a CSS file called style.css to add some margins and to center things, but it's entirely up to you if you want to include this styling file.
Speech Recognition Using the Web Speech API in JavaScript
First, create a new JavaScript file and name it speechRecognition.js. Next, add the script to the HTML file using the script tag after the body tag. Adding the script tag after the body tag will make sure that the script file is loaded after all the elements have been loaded to the DOM which aids performance.
Text to Speech Using the Web Speech API in JavaScript
speech.lang = "en"; Text: The text property gets and sets the text that will be synthesized when the utterance is spoken. The text can be provided as plain text. In our case, the text property must be set when the start button is clicked. Let's add a click listener to the button.
Building a Speech to Text App with JavaScript
Here, we programmed our application to inform the user that voice recognition is on and converts speech to text. Next, we will write code for the onresult event handler. This event is triggered when the recognition API has successfully converted speech from the user's microphone to text, and the data is made available via the event.results ...
Voice driven web apps
The new JavaScript Web Speech API makes it easy to add speech recognition to your web pages. This API allows fine control and flexibility over the speech recognition capabilities in Chrome version 25 and later. Here's an example with the recognized text appearing almost immediately while speaking. DEMO / SOURCE.
Getting started with the Speech Recognition API in Javascript
Once you verify, you can start to work with this API. Create a new instance of the webkitSpeechRecognition class and set the basic properties: // Create a new instance of SpeechRecognition. var recognition = new webkitSpeechRecognition(); // Define whether continuous results are returned for each recognition.
How to build a speech recognising app with JavaScript
Initialisation: Make your own instance of SpeechRecognition. Add this following code to your main javascript file. window.SpeechRecognition = window.SpeechRecognition || window ...
Voice Search with JavaScript (Web Speech API)
Learn how to add Speech Recognition to your websites and web applications with JavaScript, using the Web Speech API.Speech recognition involves receiving spe...
How To Build a Text-to-Speech App with Web Speech API
We will now start building our text-to-speech application. Before we begin, ensure that you have Node and npm installed on your machine. Run the following commands on your terminal to set up a project for the app and install the dependencies. Create a new project directory: mkdir web-speech-app.
Recognizing Speech with vanilla JavaScript
Setting Up our JavaScript file. Head straight into the JS section, the first thing to do is grab a text container where all messages and replies will be in and the buttons that start and stop the speech recognition process, and then we set up the window speech recognition WebKit API. After setting that up, we will create a variable that will ...
Speech Recognition in JavaScript with Code Example
In this video, I have explained the use of the Web Speech Api and the code example demonstrates how speech recognition can be done accurately using plain Jav...
How to convert speech into text using JavaScript
A text-to-speech converter is an application that is used to convert the text content entered by the user into speech with a click of a button. A text-to-speech converter should have a text area at the top so that, the user can enter a long text to be converted into speech followed by a button that converts the entered text into speech and plays th
Simple Voice Search Using Javascript Speech Recognition
The magic happens in voice.recog.onresult . We turn the spoken words into a string - let said = evt.results[0][0].transcript.toLowerCase(). Then, simply populate the search field voice.sfield.value = said, run your search process. That's all. The rest pretty much deals with the interface.
Speech Recognition App Using Vanilla JavaScript
This is the day-24 of #30days30submits. Today we are going to create a Speech Recognition App Using JavaScript web speech API. Hope you will like it. 🔔subs...
javascript
I'm trying to create an HTML5-powered voice-controlled editor using the Speech Recognition API. Currently, the problem is when you start recording, it only lasts for a certain amount of time (basically until the user stops talking).
Voice controlled ToDo List: JavaScript Speech Recognition
Finally, we start the speech input with the .start() function and call it when an input is finished. This way we achieve that the Speech Recognition API listens "permanently". recognition.addEventListener('end', recognition.start); recognition.start(); You can change this so that listening is started e.g. when you click on a button ...
7 Top Machine Learning Programming Languages
TensorFlow.js. OpnCV.js. Synaptic. To start learning how to use either of these languages, check out the links below: Java courses. JavaScript courses. 5. C++. C++ is another popular programming language widely used for performance-critical applications that need memory management and speed at the forefront.
How to Learn Speech Recognition in Java With Our API
Here we explain show how to use a speech-to-text API with two Java examples. We will be using the Rev AI API ( free for your first 5 hours) that has two different speech-to-text API's: Asynchronous API - For pre-recorded audio or video. Streaming API - For live (streaming) audio or video. Find the Full Java SDK for the Rev AI API Here.
EURASIP Journal on Audio, Speech, and Music Processing
EURASIP Journal on Audio, Speech, and Music Processing (JASM) welcomes Special Issues on timely topics related to the field of signal processing. The objective of Special Issues is to bring together recent and high quality works in a research domain, to promote key advances in theory and applications of the processing of various audio signals, with a specific focus on speech and music and to ...
Gender-Driven English Speech Emotion Recognition with Genetic ...
Speech emotion recognition based on gender holds great importance for achieving more accurate, personalized, and empathetic interactions in technology, healthcare, psychology, and social sciences. In this paper, we present a novel gender-emotion model. First, gender and emotion features were extracted from voice signals to lay the foundation for our recognition model. Second, a genetic ...
Speech Recognition with JavaScript
Speech Recognition in the Browser with JavaScript - key code blocks: /* Check whether the SpeechRecognition or the webkitSpeechRecognition API is available on window and reference it */ const recognitionSvc = window.SpeechRecognition || window.webkitSpeechRecognition; // Instantiate it const recognition = new recognitionSvc(); /* Set the speech ...
New UBC engineering research facility accelerates innovation in BC's
BC's hydrogen infrastructure enters a new era with today's launch of the $23-million Smart Hydrogen Energy District (SHED) at UBC. Equipped with a hydrogen fueling station, this facility is expected to pave the way for breakthroughs in critical energy research.
Songwriters Hall of Fame Show 2024: SZA, R.E.M., Steely Dan, More
That standard was continued in fine fashion on Thursday night at the ceremony honoring the SHOF class of 2024: R.E.M., Steely Dan, SZA, producer Timbaland and songwriters Hillary Lindsey, Diane ...
President Lula's speech during the extraordinary session of the Arab
Translated transcription of President Luiz Inácio Lula da Silva's speech during the extraordinary session of the Council of the Arab League, in Cairo, Egypt, on 15 February, 2024 ... to advocate for the recognition of the Palestinian State as a sovereign state, not only by the UN but also on the ground, so that Palestinians can build their ...