speech to text html code

Speech to Text Converter using HTML, CSS and JavaScript

Introduction :

This project is a Speech to Text Converter , which allows users to convert spoken words into written text . It consists of an HTML page with a textarea to display the converted text and a button (represented by an image) to trigger the speech recognition functionality. The project uses HTML, CSS, and JavaScript to achieve this functionality. The HTML structure establishes a visually appealing and accessible interface. The inclusion of a strategically positioned textarea within a dedicated form element ensures a user-friendly display of the converted text. The design, further enriched by CSS styles, fosters a cohesive and responsive layout suitable for various devices. At the core of this innovation lies the JavaScript logic, orchestrating the entire speech-to-text conversion process. The speechToTextConversion function serves as the linchpin, orchestrating the setup and configuration of the SpeechRecognition object. This function not only dynamically toggles between the microphone and stop button but also actively listens for speech input events. The real-time feedback provided in the textarea, coupled with intelligent error handling, ensures a robust and seamless user experience.

Explanation :

Html structure :.

• <h1> : Heading displaying “Speech to Text Converter.”
• <div id="wrapper"> : Container for the textarea.
• <form id="paper"> : Form containing the textarea for displaying converted text.
• <div class="container"> : Container for the play button and instructions.
• <img id="playButton"> : Image acting as the play button.
• <span class="instruction"> : Text with instructions.

JavaScript Logic :

• Variable i is declared and initialized to 0.
• speechToTextConversion function is defined:
• It checks for SpeechRecognition support and initializes a new SpeechRecognition object.
• Sets various properties like language, continuous recognition, etc.
• Defines a textarea element as diagnostic .
• Defines an onclick event for the play button image:
• If i is 0, it changes the image source to “record-button-thumb.png,” starts recognition, and updates i to 1.
• If i is 1, it changes the image source to “mic.png,” stops recognition, and updates i to 0.
• Sets up event listeners for recognition events ( onresult , onnomatch , onerror ).
• onresult : Updates the textarea with the recognized text.
• onnomatch : Updates the textarea with a message for unmatched speech.
• onerror : Updates the textarea with an error message.

Purpose of Functions:

speechToTextConversion Function: 

• Initialization: Checks browser support and creates a SpeechRecognition object.
• Configuration: Sets properties for continuous recognition, language, etc.
• Element Retrieval: Retrieves the textarea element for displaying converted text.
• Button Click Handling: Toggles between starting and stopping recognition when the button is clicked.  

Recognition Events Handling:

• onresult : Updates the textarea with the recognized text and logs confidence to the console.

Variable i :

• Keeps track of the state of the button (whether it’s the first or second click). This helps in determining whether to start or stop the speech recognition process.

SOURCE CODE :

Join our telegram for free coding ebooks & handwritten notes, html (index.html), speech to text converter.

CSS (style.css)

Javascript (script.js), also download the media files used in this project by clicking on the following button, conclusion :.

Your project effectively combines HTML, CSS, and JavaScript to create a simple Speech to Text Converter with a clean and user-friendly interface. Users can click the microphone button to start/stop speech recognition, and the recognized text is displayed in a textarea. The JavaScript logic ensures proper handling of recognition events and user interactions.

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• About AssemblyAI

How To Convert Voice To Text Using JavaScript

This article shows how Real-Time Speech Recognition from a microphone recording can be integrated into your JavaScript application in only a few lines of code.

Senior Developer Advocate

Real-Time Voice-To-Text in JavaScript With AssemblyAI

The easiest solution is a Speech-to-Text API , which can be accessed with a simple HTTP client in every programming language. One of the easiest to use APIs to integrate is AssemblyAI, which offers not only a traditional speech transcription service for audio files but also a real-time speech recognition endpoint that streams transcripts back to you over WebSockets within a few hundred milliseconds.

Before getting started, we need to get a working API key. You can get one here and get started for free:

Step 1: Set up the HTML code and microphone recorder

Create a file index.html and add some HTML elements to display the text. To use a microphone, we embed RecordRTC , a JavaScript library for audio and video recording.

Additionally, we embed index.js , which will be the JavaScript file that handles the frontend part. This is the complete HTML code:

Step 2: Set up the client with a WebSocket connection in JavaScript

Next, create the index.js and access the DOM elements of the corresponding HTML file. Additionally, we make global variables to store the recorder, the WebSocket, and the recording state.

Then we need to create only one function to handle all the logic. This function will be executed whenever the user clicks on the button to start or stop the recording. We toggle the recording state and implement an if-else-statement for the two states.

If the recording is stopped, we stop the recorder instance and close the socket. Before closing, we also need to send a JSON message that contains {terminate_session: true} :

Then we need to implement the else part that is executed when the recording starts. To not expose the API key on the client side, we send a request to the backend and fetch a session token.

Then we establish a WebSocket that connects with wss://api.assemblyai.com/v2/realtime/ws . For the socket, we have to take care of the events onmessage , onerror , onclose , and onopen . In the onmessage event we parse the incoming message data and set the inner text of the corresponding HTML element.

In the onopen event we initialize the RecordRTC instance and then send the audio data as base64 encoded string. The other two events can be used to close and reset the socket. This is the remaining code for the else block:

Try AssemblyAI's Real-Time Transcription

Experience the power of our Speech-to-Text API without writing any code. Test it now in our interactive playground.

Step 3: Set up a server with Express.js to handle authentication

Lastly, we need to create another file server.js that handles authentication. Here we create a server with one endpoint that creates a temporary authentication token by sending a POST request to https://api.assemblyai.com/v2/realtime/token .

To use it, we have to install Express.js , Axios , and cors :

And this is the full code for the server part:

This endpoint on the backend will send a valid session token to the frontend whenever the recording starts. And that's it! You can find the whole code in our GitHub repository .

Run the JavaScript files for Real-Time Voice and Speech Recognition

Now we must run the backend and frontend part. Start the server with

And then serve the frontend site with the serve package :

Now you can visit http://localhost:3000 , start the voice recording, and see the real-time transcription in action!

Real-Time Transcription Video Tutorial

Watch our video tutorial to see an example of real-time transcription:

Ready to Build with Real-Time Transcription?

Sign up now to get your API key and start integrating AssemblyAI's powerful Speech-to-Text capabilities into your applications.

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Using the Web Speech API

Speech recognition.

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.

The Web Speech API has a main controller interface for this — SpeechRecognition — plus a number of closely-related interfaces for representing grammar, results, etc. Generally, the default speech recognition system available on the device will be used for the speech recognition — most modern OSes have a speech recognition system for issuing voice commands. Think about Dictation on macOS, Siri on iOS, Cortana on Windows 10, Android Speech, etc.

Note: On some browsers, such as Chrome, using Speech Recognition on a web page involves a server-based recognition engine. Your audio is sent to a web service for recognition processing, so it won't work offline.

To show simple usage of Web speech recognition, we've written a demo called Speech color changer . When the screen is tapped/clicked, you can say an HTML color keyword, and the app's background color will change to that color.

To run the demo, navigate to the live demo URL in a supporting mobile browser (such as Chrome).

HTML and CSS

The HTML and CSS for the app is really trivial. We have a title, instructions paragraph, and a div into which we output diagnostic messages.

The CSS provides a very simple responsive styling so that it looks OK across devices.

Let's look at the JavaScript in a bit more detail.

Prefixed properties

Browsers currently support speech recognition with prefixed properties. Therefore at the start of our code we include these lines to allow for both prefixed properties and unprefixed versions that may be supported in future:

The grammar

The next part of our code defines the grammar we want our app to recognize. The following variable is defined to hold our grammar:

The grammar format used is JSpeech Grammar Format ( JSGF ) — you can find a lot more about it at the previous link to its spec. However, for now let's just run through it quickly:

• The lines are separated by semicolons, just like in JavaScript.
• The first line — #JSGF V1.0; — states the format and version used. This always needs to be included first.
• The second line indicates a type of term that we want to recognize. public declares that it is a public rule, the string in angle brackets defines the recognized name for this term ( color ), and the list of items that follow the equals sign are the alternative values that will be recognized and accepted as appropriate values for the term. Note how each is separated by a pipe character.
• You can have as many terms defined as you want on separate lines following the above structure, and include fairly complex grammar definitions. For this basic demo, we are just keeping things simple.

Plugging the grammar into our speech recognition

The next thing to do is define a speech recognition instance to control the recognition for our application. This is done using the SpeechRecognition() constructor. We also create a new speech grammar list to contain our grammar, using the SpeechGrammarList() constructor.

We add our grammar to the list using the SpeechGrammarList.addFromString() method. This accepts as parameters the string we want to add, plus optionally a weight value that specifies the importance of this grammar in relation of other grammars available in the list (can be from 0 to 1 inclusive.) The added grammar is available in the list as a SpeechGrammar object instance.

We then add the SpeechGrammarList to the speech recognition instance by setting it to the value of the SpeechRecognition.grammars property. We also set a few other properties of the recognition instance before we move on:

• SpeechRecognition.continuous : Controls whether continuous results are captured ( true ), or just a single result each time recognition is started ( false ).
• SpeechRecognition.lang : Sets the language of the recognition. Setting this is good practice, and therefore recommended.
• SpeechRecognition.interimResults : Defines whether the speech recognition system should return interim results, or just final results. Final results are good enough for this simple demo.
• SpeechRecognition.maxAlternatives : Sets the number of alternative potential matches that should be returned per result. This can sometimes be useful, say if a result is not completely clear and you want to display a list if alternatives for the user to choose the correct one from. But it is not needed for this simple demo, so we are just specifying one (which is actually the default anyway.)

Starting the speech recognition

After grabbing references to the output <div> and the HTML element (so we can output diagnostic messages and update the app background color later on), we implement an onclick handler so that when the screen is tapped/clicked, the speech recognition service will start. This is achieved by calling SpeechRecognition.start() . The forEach() method is used to output colored indicators showing what colors to try saying.

Receiving and handling results

Once the speech recognition is started, there are many event handlers that can be used to retrieve results, and other pieces of surrounding information (see the SpeechRecognition events .) The most common one you'll probably use is the result event, which is fired once a successful result is received:

The second line here is a bit complex-looking, so let's explain it step by step. The SpeechRecognitionEvent.results property returns a SpeechRecognitionResultList object containing SpeechRecognitionResult objects. It has a getter so it can be accessed like an array — so the first [0] returns the SpeechRecognitionResult at position 0. Each SpeechRecognitionResult object contains SpeechRecognitionAlternative objects that contain individual recognized words. These also have getters so they can be accessed like arrays — the second [0] therefore returns the SpeechRecognitionAlternative at position 0. We then return its transcript property to get a string containing the individual recognized result as a string, set the background color to that color, and report the color recognized as a diagnostic message in the UI.

We also use the speechend event to stop the speech recognition service from running (using SpeechRecognition.stop() ) once a single word has been recognized and it has finished being spoken:

Handling errors and unrecognized speech

The last two handlers are there to handle cases where speech was recognized that wasn't in the defined grammar, or an error occurred. The nomatch event seems to be supposed to handle the first case mentioned, although note that at the moment it doesn't seem to fire correctly; it just returns whatever was recognized anyway:

The error event handles cases where there is an actual error with the recognition successfully — the SpeechRecognitionErrorEvent.error property contains the actual error returned:

Speech synthesis

Speech synthesis (aka text-to-speech, or TTS) involves receiving synthesizing text contained within an app to speech, and playing it out of a device's speaker or audio output connection.

The Web Speech API has a main controller interface for this — SpeechSynthesis — plus a number of closely-related interfaces for representing text to be synthesized (known as utterances), voices to be used for the utterance, etc. Again, most OSes have some kind of speech synthesis system, which will be used by the API for this task as available.

To show simple usage of Web speech synthesis, we've provided a demo called Speak easy synthesis . This includes a set of form controls for entering text to be synthesized, and setting the pitch, rate, and voice to use when the text is uttered. After you have entered your text, you can press Enter / Return to hear it spoken.

To run the demo, navigate to the live demo URL in a supporting mobile browser.

The HTML and CSS are again pretty trivial, containing a title, some instructions for use, and a form with some simple controls. The <select> element is initially empty, but is populated with <option> s via JavaScript (see later on.)

Let's investigate the JavaScript that powers this app.

Setting variables

First of all, we capture references to all the DOM elements involved in the UI, but more interestingly, we capture a reference to Window.speechSynthesis . This is API's entry point — it returns an instance of SpeechSynthesis , the controller interface for web speech synthesis.

Populating the select element

To populate the <select> element with the different voice options the device has available, we've written a populateVoiceList() function. We first invoke SpeechSynthesis.getVoices() , which returns a list of all the available voices, represented by SpeechSynthesisVoice objects. We then loop through this list — for each voice we create an <option> element, set its text content to display the name of the voice (grabbed from SpeechSynthesisVoice.name ), the language of the voice (grabbed from SpeechSynthesisVoice.lang ), and -- DEFAULT if the voice is the default voice for the synthesis engine (checked by seeing if SpeechSynthesisVoice.default returns true .)

We also create data- attributes for each option, containing the name and language of the associated voice, so we can grab them easily later on, and then append the options as children of the select.

Older browser don't support the voiceschanged event, and just return a list of voices when SpeechSynthesis.getVoices() is fired. While on others, such as Chrome, you have to wait for the event to fire before populating the list. To allow for both cases, we run the function as shown below:

Speaking the entered text

Next, we create an event handler to start speaking the text entered into the text field. We are using an onsubmit handler on the form so that the action happens when Enter / Return is pressed. We first create a new SpeechSynthesisUtterance() instance using its constructor — this is passed the text input's value as a parameter.

Next, we need to figure out which voice to use. We use the HTMLSelectElement selectedOptions property to return the currently selected <option> element. We then use this element's data-name attribute, finding the SpeechSynthesisVoice object whose name matches this attribute's value. We set the matching voice object to be the value of the SpeechSynthesisUtterance.voice property.

Finally, we set the SpeechSynthesisUtterance.pitch and SpeechSynthesisUtterance.rate to the values of the relevant range form elements. Then, with all necessary preparations made, we start the utterance being spoken by invoking SpeechSynthesis.speak() , passing it the SpeechSynthesisUtterance instance as a parameter.

In the final part of the handler, we include a pause event to demonstrate how SpeechSynthesisEvent can be put to good use. When SpeechSynthesis.pause() is invoked, this returns a message reporting the character number and name that the speech was paused at.

Finally, we call blur() on the text input. This is mainly to hide the keyboard on Firefox OS.

Updating the displayed pitch and rate values

The last part of the code updates the pitch / rate values displayed in the UI, each time the slider positions are moved.

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.

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 .

You may also like:

• JavaScript Window Object
• JavaScript Number Object
• JavaScript Functions
• JavaScript Document Object

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Related posts.

Converting from Speech to Text with JavaScript

In this tutorial we are going to experiment with the Web Speech API . It's a very powerful browser interface that allows you to record human speech and convert it into text. We will also use it to do the opposite - reading out strings in a human-like voice.

Let's jump right in!

To showcase the ability of the API we are going to build a simple voice-powered note app. It does 3 things:

• Takes notes by using voice-to-text or traditional keyboard input.
• Saves notes to localStorage.
• Shows all notes and gives the option to listen to them via Speech Synthesis.

We won't be using any fancy dependencies, just good old jQuery for easier DOM operations and Shoelace for CSS styles. We are going to include them directly via CDN, no need to get NPM involved for such a tiny project.

The HTML and CSS are pretty standard so we are going to skip them and go straight to the JavaScript. To view the full source code go to the Download button near the top of the page.

Speech to Text

The Web Speech API is actually separated into two totally independent interfaces. We have SpeechRecognition for understanding human voice and turning it into text (Speech -> Text) and SpeechSynthesis for reading strings out loud in a computer generated voice (Text -> Speech). We'll start with the former.

The Speech Recognition API is surprisingly accurate for a free browser feature. It recognized correctly almost all of my speaking and knew which words go together to form phrases that make sense. It also allows you to dictate special characters like full stops, question marks, and new lines.

The first thing we need to do is check if the user has access to the API and show an appropriate error message. Unfortunately, the speech-to-text API is supported only in Chrome and Firefox (with a flag), so a lot of people will probably see that message.

The recognition variable will give us access to all the API's methods and properties. There are various options available but we will only set recognition.continuous to true. This will enable users to speak with longer pauses between words and phrases.

Before we can use the voice recognition, we also have to set up a couple of event handlers. Most of them simply listen for changes in the recognition status:

There is, however, a special onresult event that is very crucial. It is executed every time the user speaks a word or several words in quick succession, giving us access to a text transcription of what was said.

When we capture something with the onresult handler we save it in a global variable and display it in a textarea:

The above code is slightly simplified. There is a very weird bug on Android devices that causes everything to be repeated twice. There is no official solution yet but we managed to solve the problem without any obvious side effects. With that bug in mind the code looks like this:

Once we have everything set up we can start using the browser's voice recognition feature. To start it simply call the start() method:

This will prompt users to give permission. If such is granted the device's microphone will be activated.

Most APIs that require user permission don't work on non-secure hosts. Make sure you are serving your Web Speech apps over HTTPS.

The browser will listen for a while and every recognized phrase or word will be transcribed. The API will stop listening automatically after a couple seconds of silence or when manually stopped.

With this, the speech-to-text portion of our app is complete! Now, let's do the opposite!

Text to Speech

Speech Synthesys is actually very easy. The API is accessible through the speechSynthesis object and there are a couple of methods for playing, pausing and other audio related stuff. It also has a couple of cool options that change the pitch, rate, and even the voice of the reader.

All we will actually need for our demo is the speak() method. It expects one argument, an instance of the beautifully named SpeechSynthesisUtterance class.

Here is the entire code needed to read out a string.

When this function is called, a robot voice will read out the given string, doing it's best human impression.

In an era where voice assistants are more popular then ever, an API like this gives you a quick shortcut to building bots that understand and speak human language.

Adding voice control to your apps can also be a great form of accessibility enhancement. Users with visual impairment can benefit from both speech-to-text and text-to-speech user interfaces.

The speech synthesis and speech recognition APIs work pretty well and handle different languages and accents with ease. Sadly, they have limited browser support for now which narrows their usage in production. If you need a more reliable form of speech recognition, take a look at these third-party APIs:

• Google Cloud Speech API
• Bing Speech API
• CMUSphinx and it's JavaScript version Pocketsphinx (both open-source).
• API.AI - Free Google API powered by Machine Learning

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Excellent article and very easy to follow.

I got to thinking, why not add CKEditor to the textarea and did so after downloading demo. Everything looks good, even the recording works and notes can be saved. BUT, the spoken wrods are not appearing in the CKEditor area.

When you have time, could you possible cover getting your tutorial working with CKEditor? Be a really nice addition to have:)

Thanks for sharing your notes tutorial!

THIS IS MY CURRENT ISSUE RIGHT NOW. DID YOU SOLVED IT MAN ?

Great tutorial! Just wondering why doesn't the Start Recognition button work if I copy the code to a Codeanywhere project?

excellent article. i didn't have idea that such API exists in browser. tried example in chrome , worked fine. how this work for non-english speaking language?

Both text-to-speech and speech-to-text work pretty well with other languages.

For speech recognition you have to set the recognition.lang property .

With speech synthesis you can change the speaking voice. There is a large list of different languages to choose from - getVoices .

Sorry, it doesn't work.

It's problem with your secure connection. Check Is it https or not ?

This is working excellent on my local server i have implemented this and uploaded it on hosting server when i start the recognition the page says , this page is always blocked from using the microphone . Can you help me ?

i am working on speech recognition for Android applications. please suggest me can i use it in android and how can i get jar file for artyom.js?

Nice tutorial!

Is there a way to change language for the recognizer?

previously I had one already developed, but this one started to give me problems in the activation of the microphone, so I've been looking for solutions, I see that this example works very well, but when downloading the code and even make a copy and use the current one, it does not work for me, I put it on my server and nothing, so I tried to put it in a hosting to see if the server was the problem, and in the same way it does not connect, the microphone is not activated, which is what I will be missing for that this example works well, since I can not make functional the activation of the microphone, unless it enters by localhost, there is its that allows me to activate the microphone.

Firefox (with a flag) what about flag ?

It's working perfectly fine on Chrome... but, what changes we need to do so that it will work on all browsers..

Excellent articles and easy to understand and also easy to implement

why doesn't the Start Recognition button work if I copy the code in visual studio code ?

this is great 💥💥💥

great tutorial and library thank you so much for it, but actually i have problem when recognizing languages other than English have you made this library to work with other languages. my case: i am trying to recognize Arabic and turn an Arabic speech to text but the Arabic written in English letters and that is not correct

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How to convert speech to text using JavaScript?

To convert the spoken words to the text we generally use the Web Speech API’s component that is “SpeechRecognition” . The SpeechRecognition component recognizes the spoken words in the form of audio and converts them to the text. The spoken words are stored in it in an array which are then displayed inside the HTML element on the browser screen.

The basic syntax used in is −

We can also use SpeechRecognition() instead of webkitSpeechRecognition() as webkitSpeechRecognition() is used in chrome and apple safari browser for speech recognition.

Step 1 − Create a HTML page as given below, create a HTML button using <button> tag. Add an onclick event in it with the function name “runSpeechRecog()”. Also create a <p> tag with id “action” in it.

Step 2 − Create a runSpeechRecog() arrow function inside a script tag as we are using internal javascript.

Step 3 − Select the “p” tag of HTML using Document Object Model (DOM) as document.getElementById(). Store it in a variable.

Step 4 − Create an object of a webkitSpeechRecognition() constructor and store it in a reference variable. So that all the methods of webkitSpeechRecognition() class will be in the reference variable.

Step 5 − Use “recognition.onstart()“, this function will return the action when the recognition is started.

Step 6 − Now use recognition.onresult() to display the spoken words on the screen.

Step 7 − Use the recognition.start() method to start the speech recognition.

Description

When the “runSpeechRecog()” function is triggered the webkitSpeechRecognition() is initialized and all the properties of this are stored in the reference and shows the below output as the browser is ready to listen to the user's spoken words.

When the user has stopped speaking the sentence, the result is stored in the form of an array of words. Then these words are returned as a transcript of a sentence on the user browser screen. For example a user runs this speech to text program on its browser and presses the speech button and start speaking as “tutorialpoint.com”, as user stops speaking the speech recognition program will stop and will display the transcript on the browser as “tutorialpoint.com”.

The Web Speech API of JavaScript is used in many types of applications. As the web speech api has two different components as SpeechRecognition API which is used for speech-text conversion and SpeechSynthesis API which is used for text-speech conversion. The above SpeechRecognition is supported for the browser Chrome, Apple Safari, Opera.

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Build a Text to Speech Converter using HTML, CSS & 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 the sound on click to it. In this article, we will build a fully responsive text-to-speech converter using HTML , CSS , and JavaScript .

• Create a folder with the project name and create the required HTML, CSS, and JavaScript files as shown in the project structure.
• Now, use the HTML tags like textarea, button, div, head, body etc. to define the structure of the website.
• Add the styles to the HTML tags used to define the structure by selecting them with the help of given IDs and Classes.
• Utilise the speechSynthesis API of the global window object and the SpeechSynthesisUtterance to create a utteraance of the entered text.
• Next, use the speak() method of the speechSynthesis API to speak or play the created utterance as a speech.
• Handle the errors efficiently if user have not provided any text to convert.

Example: The below example will help you to understand the process of creating an text-to-speech converter using HTML, CSS, and JavaScript:

Final Output

Note: You will not able to hear the voice as it is an gif so kindly run this project locally on any Online IDE(Replit, etc.)

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Using the Speech-to-Text API with Node.js

1. overview.

Google Cloud Speech-to-Text API enables developers to convert audio to text in 120 languages and variants, by applying powerful neural network models in an easy to use API.

In this codelab, you will focus on using the Speech-to-Text API with Node.js. You will learn how to send an audio file in English and other languages to the Cloud Speech-to-Text API for transcription.

What you'll learn

• How to enable the Speech-to-Text API
• How to Authenticate API requests
• How to install the Google Cloud client library for Node.js
• How to transcribe audio files in English
• How to transcribe audio files with word timestamps
• How to transcribe audio files in different languages

What you'll need

• A Google Cloud Platform Project
• A Browser, such Chrome or Firefox
• Familiarity using Javascript/Node.js

How will you use this tutorial?

How would you rate your experience with node.js, how would you rate your experience with using google cloud platform services, 2. setup and requirements, self-paced environment setup.

• Sign in to Cloud Console and create a new project or reuse an existing one. (If you don't already have a Gmail or G Suite account, you must create one .)

Remember the project ID, a unique name across all Google Cloud projects (the name above has already been taken and will not work for you, sorry!). It will be referred to later in this codelab as PROJECT_ID .

• Next, you'll need to enable billing in Cloud Console in order to use Google Cloud resources.

Running through this codelab shouldn't cost much, if anything at all. Be sure to to follow any instructions in the "Cleaning up" section which advises you how to shut down resources so you don't incur billing beyond this tutorial. New users of Google Cloud are eligible for the $300USD Free Trial program.

Start Cloud Shell

While Google Cloud can be operated remotely from your laptop, in this codelab you will be using Google Cloud Shell , a command line environment running in the Cloud.

Activate Cloud Shell

If you've never started Cloud Shell before, you'll be presented with an intermediate screen (below the fold) describing what it is. If that's the case, click Continue (and you won't ever see it again). Here's what that one-time screen looks like:

It should only take a few moments to provision and connect to Cloud Shell.

This virtual machine is loaded with all the development tools you'll need. It offers a persistent 5GB home directory and runs in Google Cloud, greatly enhancing network performance and authentication. Much, if not all, of your work in this codelab can be done with simply a browser or your Chromebook.

Once connected to Cloud Shell, you should see that you are already authenticated and that the project is already set to your project ID.

• Run the following command in Cloud Shell to confirm that you are authenticated:

Command output

If it is not, you can set it with this command:

3. Enable the Speech-to-Text API

Before you can begin using the Speech-to-Text API, you must enable the API. You can enable the API by using the following command in the Cloud Shell:

4. Authenticate API requests

In order to make requests to the Speech-to-Text API, you need to use a Service Account . A Service Account belongs to your project and it is used by the Google Client Node.js library to make Speech-to-Text API requests. Like any other user account, a service account is represented by an email address. In this section, you will use the Cloud SDK to create a service account and then create credentials you will need to authenticate as the service account.

First, set an environment variable with your PROJECT_ID which you will use throughout this codelab, if you are using Cloud Shell this will be set for you:

Next, create a new service account to access the Speech-to-Text API by using:

Next, create credentials that your Node.js code will use to login as your new service account. Create these credentials and save it as a JSON file ~/key.json by using the following command:

Finally, set the GOOGLE_APPLICATION_CREDENTIALS environment variable, which is used by the Speech-to-Text API Node.js library, covered in the next step, to find your credentials. The environment variable should be set to the full path of the credentials JSON file you created, by using:

You can read more about authenticating the Speech-to-Text API .

5. Install the Google Cloud Speech-to-Text API client library for Node.js

First, create a project that you will use to run this Speech-to-Text API lab, initialize a new Node.js package in a folder of your choice:

NPM asks several questions about the project configuration, such as name and version. For each question, press ENTER to accept the default values. The default entry point is a file named index.js .

Next, install the Google Cloud Speech library to the project:

For more instructions on how to set up a Node.js development for Google Cloud please see the Setup Guide .

Now, you're ready to use Speech-to-Text API!

6. Transcribe Audio Files

In this section, you will transcribe a pre-recorded audio file in English. The audio file is available on Google Cloud Storage.

Navigate to the index.js file inside the and replace the code with the following:

Take a minute or two to study the code and see it is used to transcribe an audio file*.*

The Encoding parameter tells the API which type of audio encoding you're using for the audio file. Flac is the encoding type for .raw files (see the doc for encoding type for more details).

In the RecognitionAudio object, you can pass the API either the uri of our audio file in Cloud Storage or the local file path for the audio file. Here, we're using a Cloud Storage uri.

Run the program:

You should see the following output:

7. Transcribe with word timestamps

Speech-to-Text can detect time offset (timestamp) for the transcribed audio. Time offsets show the beginning and end of each spoken word in the supplied audio. A time offset value represents the amount of time that has elapsed from the beginning of the audio, in increments of 100ms.

Take a minute or two to study the code and see it is used to transcribe an audio file with word timestamps*.* The EnableWordTimeOffsets parameter tells the API to enable time offsets (see the doc for more details).

Run your program again:

8. Transcribe different languages

Speech-to-Text API supports transcription in over 100 languages! You can find a list of supported languages here .

In this section, you will transcribe a pre-recorded audio file in French. The audio file is available on Google Cloud Storage.

Run your program again and you should see the following output:

This is a sentence from a popular French children's tale .

For the full list of supported languages and language codes, see the documentation here .

9. Congratulations!

You learned how to use the Speech-to-Text API using Node.js to perform different kinds of transcription on audio files!

To avoid incurring charges to your Google Cloud Platform account for the resources used in this quickstart:

• Go to the Cloud Platform Console .
• Select the project you want to shut down, then click ‘Delete' at the top: this schedules the project for deletion.
• Google Cloud Speech-to-Text API: https://cloud.google.com/speech-to-text/docs
• Node.js on Google Cloud Platform: https://cloud.google.com/nodejs/
• Google Cloud Node.js client: https://googlecloudplatform.github.io/google-cloud-node/

This work is licensed under a Creative Commons Attribution 2.0 Generic License.

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.

Text to speech in the browser with the Web Speech API

Time to read: 5 minutes

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The Web Speech API has two functions, speech synthesis , otherwise known as text to speech, and speech recognition . With the SpeechSynthesis API we can command the browser to read out any text in a number of different voices.

From a vocal alerts in an application to bringing an Autopilot powered  chatbot to life on your website, the Web Speech API has a lot of potential for web interfaces. Follow on to find out how to get your web application speaking back to you.

What you'll need

If you want to build this application as we learn about the SpeechSynthesis API then you'll need a couple of things:

• A modern browser ( the API is supported across the majority of desktop and mobile browsers )
• A text editor

Once you're ready, create a directory to work in and download this HTML file  and this CSS file  to it. Make sure they are in the same folder and the CSS file is named style.css . Open the HTML file in your browser and you should see this:

Let's get started with the API by getting the browser to talk to us for the first time.

The Speech Synthesis API

Before we start work with this small application, we can get the browser to start speaking using the browser's developer tools. On any web page, open up the developer tools console and enter the following code:

Your browser will speak the text " Hello, this is your browser speaking. " in its default voice. We can break this down a bit though.

We created a SpeechSynthesisUtterance which contained the text we wanted to be spoken. Then we passed the utterance to the speak method of the speechSynthesis object. This queues up the utterance to be spoken and then starts the browser speaking. If you send more than one utterance to the speak method they will be spoken one after another.

Let's take the starter code we downloaded earlier and turn this into a small app where we can input the text to be spoken and choose the voice that the browser says it in.

Speech Synthesis in a web application

Open up the HTML file you downloaded earlier in your text editor. We'll start by connecting the form up to speak whatever you enter in the text input when you submit. Later, we'll add the ability to choose the voice to use.

Between the <script> tags at the bottom of the HTML we'll start by listening for the DOMContentLoaded event and then selecting some references to the elements we'll need.

We then need to listen to the submit event on the form and when it fires, grab the text from the input. With that text we'll create a SpeechSynthesisUtterance and then pass it to speechSynthesis.speak . Finally, we empty the input box and wait for the next thing to say.

Open the HTML in your browser and enter some text in the input. You can ignore the <select> box at this point, we'll use that in the next section. Hit " Say it " and listen to the browser read out your words.

It's not much code to get the browser to say something, but what if we want to pick the voice that it uses. Let's populate the dropdown on the page with the available voices and use it to select the one we want to use.

Picking voices for text to speech

We need to get references to the <select> element on the page and initialise a couple of variables we'll use to store the available voices and the current voice we are using. Add this to the top of the script:

Next up we need to populate the select element with the available voices. We'll create a new function to do this, as we might want to call it more than once (more on that in a bit). We can call on speechSynthesis.getVoices() to return the available SpeechSynthesisVoice objects .

Whilst we are populating the voice options we should also detect the currently selected voice. If we have already chosen a voice we can check against our currentVoice object and if we haven't yet chosen a voice then we can detect the default voice with the voice.default property.

We can call populateVoice straight away. Some browsers will load the voices page load and will return their list straight away. Other browsers need to load their list of voices asynchronously and will emit a "voiceschanged" event once they have loaded. Some browsers do not emit this event at all though.

To account for all the potential scenarios we'll call populateVoices immediately and also set it as the callback to the "voiceschanged" event.

Reload the page and you will see the <select> element populated with all the available voices, including the language the voice supports. We haven't hooked up selecting and using the voice yet though, that comes next.

Listen to the "change" event of the select element and whenever it is fired, select the currentVoice using the selectedIndex of the <select> element.

Now, to use the voice with the speech utterance we need to set the voice on the utterance that we create.

Reload the page and play around selecting different voices and saying different things.

Bonus: build a visual speaking indicator

We've built a speech synthesiser that can use different voices, but I wanted to throw one more thing in for fun. Speech utterances emit a number of events  that you can use to make your application respond to speech. To finish this little app off we're going to make an animation show as the browser is speaking. I've already added the CSS for the animation  so to activate it we need to add a "speaking" class to the <main> element while the browser is speaking.

Grab a reference to the <main> element at the top of the script:

Now, we can listen to the start and end events of the utterance to add and remove the "speaking" class. But, if we remove the class in the middle of the animation it won't fade out smoothly, so we should listen for the end of the animation's iteration, using the "animationiteration" event , and then remove the class.

Now when you start the browser talking the background will pulse blue and when the utterance is over it will stop.

Your browser is getting chatty

In this post you've seen how to get started and work with the Speech Synthesis API  from the Web Speech API . All the code for this application can be found on GitHub  and you can see it in action or remix it on Glitch .

I'm excited about the potential of this API for building my own in browser bots, so look out for more of this in the future.

Have you used the Speech Synthesis API or have any plans for it? I'd love to hear in the comments below, or drop me a note at philnash@twilio.com  or on Twitter at @philnash .

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CodeWithRandom

Speech to Text Using HTML,CSS and JavaScript With Source Code

• Post author: admin
• Post published: February 10, 2023
• Post category: clone project / HTML & CSS / Html & CSS Project / javascript project / Project
• Post comments: 0 Comments

Welcome to The Codewithrandom blog. This blog teaches us how we create a Speech To Text Using JavaScript. We use Html for creating a Structure for the project and use Css for styling Speech To Text and finally, we add JavaScript for Speech To Text functionality.

We use SpeechRecognition’s inbuilt JavaScript API to get speech. then write code for Show Speech Text that we Speak. Then Use If/Else to move div with our voice that is captured by Voice Api and add That Functionality to detect what we speak Like Left or right and div moves according to voice.

50+ HTML, CSS & JavaScript Projects With Source Code

Table of Contents

HTML Code For Speech To Text

There is all the Html code for the Speech To Text. Now, you can see output without Css and Javascript. then we write Css and JavaScript for the Speech To Text.

Ecommerce Website Using Html Css And Javascript Source Code

Only HTML Code Output

CSS Code For Speech To Text

50+ Html ,Css & Javascript Projects With Source Code

HTML + CSS Updated output

JavaScript Code For Speech To Text

Final output of speech to text using javascript.

Now that we have completed our Speech To Text. Our updated output with Html, Css, and JavaScript. Hope you like the Speech Text Project. you can see the output video and project screenshots. See our other blogs and gain knowledge in front-end development.

100+ JavaScript Projects With Source Code ( Beginners to Advanced)

This post teaches us how to create a Speech To Text using simple HTML, CSS, and JavaScript. If we made a mistake or any confusion, please drop a comment to reply or help you in easy learning.

Written by – Code With Random/Anki

Code By – DM For Credit

Which code editor do you use for this Speech to Text coding?

I personally recommend using VS Code Studio, it’s straightforward and easy to use.

is this project responsive or not?

Yes! this is a responsive project

Do you use any external links to create this project?

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Add voices to any video. Generate semi-automatic voice-overs for your videos from text, in 13 languages. Use a YouTube URL or upload your own MP4 and apply text-to-speech in the easy to use editor.

WHAT ARE YOU LOOKING FOR?

ResponsiveVoice is not built for this purpose, however if you host your text or notes as webpages on your own website you can add ResponsiveVoice to your site and listen content that way.

ResponsiveVoice supports reading HTML webpages, you may convert your documents or PDFs to webpages on your own website and then add ResponsiveVoice to your site as a solution.

ResponsiveVoice generates AI speech in real-time, it does not generate mp3 or downloadable audio files. Just add the ResponsiveVoice script to your blog and you can have any blog page or post spoken out loud.

You can create AI voice overs for videos here  Text2VoiceOver

ResponsiveVoice is built specifically for this case, sign-up for the free service, get your unique code and add it to your website to instantly enable an AI voice for your website visitors.

ResponsiveVoice is created for website owners to add AI voice features to their own site. It is not a tool to read every website you visit while browsing.

ResponsiveVoice is perfect for use with queue management systems for announcing tickets with an AI voice. ResponsiveVoice is a text-to-speech library. Contact us if you have a specific need for speech recognition or speech-to-text. ResponsiveVoice is perfect for use with queue management systems for announcing tickets with an AI voice.

ResponsiveVoice is a JavaScript library, it will work in any WebView in an App. ResponsiveVoice does require an internet connection to operate.

ResponsiveVoice is the perfect choice for quickly adding accessibility AI voice features to your website. Sign-up, add the unique code to your website and allow all your visitors to enjoy your content.

ResponsiveVoice is the prefect solution for having articles read out loud on your own website. Text to speech is generated in real-time so no transmission or management of audio files is needed. It couldn’t be simpler!

ResponsiveVoice is perfect for use with queue management systems for announcing tickets with an AI voice.

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Add one line of code to your site or app

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Free for Non-Commercial

Do you want to use ResponsiveVoice for a non-commercial personal or non-profit project?

1.  WordPress Plugin  (free for commercial and non-commercial use) 2.  ResponsiveVoice Free  ( feature limited  for commercial and free for non-commercial use) 3.  AI Voice API  (free for non-commercial use only)

All other ResponsiveVoice products require paid licenses.

Just add the attribution to your site:

If you have questions about the Non-commercial license  contact us

How does it work?

Browser & device support.

Don’t Clog the Tubes!

HTML5 introduces the Speech API for AI Speech Synthesis and Speech Recognition.

This is the easiest way to use the spoken word in your app or website.

AI Speech Synthesis or more commonly known as Text To Speech (TTS) is now available in most modern browsers.

Gone are the days of waiting for Text To Speech engines to render MP3 audio files from text and then download them from servers.

Today the browser can instantly speak text on the client side and with quite reasonable quality.

Gargling Bagpipes

But there is a problem, each browser and device can have a different set of “AI Voices”. You can’t be sure of a consistent user experience when it comes to the spoken voice or accent.

If you make a call to the AI speak API using the default AI voice it will sound very different on different users devices and browsers. In some cases you won’t even know if the user will get a male or female AI voice.

Although, you make a direct call to the AI speak API and choose a specific voice like “Google UK Female”, if a user is browsing on iOS with Safari the AI voice will not be available.

Responsive Design for AI Voice

Taking inspiration from Responsive Web Design we have created responsivevoice.js a library that can easily be included in a web page that allows you to make simple api calls to speak text.

Responsive AI Voices

ResponsiveVoice JS defines a selection of smart AI Voice profiles that know which AI voice to use for the users device in order to create a consistent experience no matter which browser or device the speech is being spoken on.

By choosing one ResponsiveVoice the closest AI voice is chosen on

• iOS (Safari & Chrome)
• Android (Chrome, Including across the popular Text To Speech engines Ivona, Acapela, Samsung)
• Windows (Chrome Desktop)
• Mac OSX (Safari & Chrome)

Smart Chunking

With large blocks of text ResponsiveVoice splits up the text into chunks, with preference given to splitting at the end of sentences. Preference is given to splitting at full stop, question mark, colon or semi-colon after that split is performed by the nearest comma and falling back from that the nearest space between words.

ResponsiveVoice JS also takes care of a number of hindrances from the various implementations of HTML5 Speech API across browsers and operating systems.

• Chrome desktop has a limit on the number of characters it can speak, under the hood ResponsiveVoice JS automatically chunks text into acceptable blocks
• Chrome desktop will not speak unless initialised after page load, ResponsiveVoice JS resolves this
• iOS Safari & Chrome require timing delays between AI speech API calls, ResponsiveVoice JS resolves this
• iOS TTS can’t be triggered without a direct user interaction, ResponsiveVoice JS resolves this
• Internet Explorer speech rate is slower, ResponsiveVoice JS resolves this

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Posted on Apr 2, 2022

Text To Speech Converter in HTML CSS & JavaScript

Today in this blog, you’ll learn how to create a Text To Speech Converter using HTML CSS & JavaScript. create a Text To Speech Converter Web Application.

Text To Speech (TTS) is a technology that enables your text to be converted into speech sounds. In this project (Text To Speech Converter App), you can convert your text into speech on different voices. A pause and resume option is also available if your text character length is more than 80. I made it using HTML CSS & Vanilla JavaScript. No external JavaScript libraries or APIs are used to make this TTS App and I hope you have liked this project.

If you liked it and want to get source codes of this Text To Speech Converter App then you can copy or download coding files from the bottom of this page. But before you go to download the codes, let’s understand the main JS codes and concepts behind creating this project.

In the JavaScript code, first, I got the user text and call a function textToSpeech() with passing user text as an argument. Inside this function, using the speech synthesis property of the window object, I converted the entered text to speech. Speech Synthesis is a web speech API that controls the speech service.

After this, I got all available voices from the user device using the getVoices() method of Speech Synthesis and insert it into HTML select tag.

* Text To Speech Converter in JavaScript *

To create this Text To Speech Converter App (TTS). First, you need to create three Files:

After creating these files just paste the given codes into your file. You can also download the source code files of this Text To Speech App from the github.

First, create an HTML file with the name of index.html and paste the given codes in your HTML file. Remember, you’ve to create a file with .html extension.

Second, create a CSS file with the name of style.css and paste the given codes in your CSS file. Remember, you’ve to create a file with .css extension.

Last, create a JavaScript file with the name of script.js and paste the given codes in your JavaScript file. Remember, you’ve to create a file with .js extension.

That’s all, now you’ve successfully created a Text To Speech Converter App in HTML CSS & JavaScript. click the link to view

Text To Speech Converter

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Very good How can download This voice after created

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To make the code snippets easier to read, we can add some extra CSS styling. This includes things like changing the background color, adding padding, and choosing a specific font family.

How to Convert HTML Code to Text Format Using JavaScript

To convert HTML code into text format for embedding code snippets using JavaScript, be sure to escape special characters to display them as text instead of HTML. Here is a simple JavaScript function HTML to text

1, Create a function to escape HTML characters:

This function replaces <, &, > special HTML characters with their corresponding HTML entities to ensure they are displayed correctly in the browser

2, Use this function to convert your HTML code to a text format

ElevenLabs’ text-to-speech app Reader is now available globally

ElevenLabs , a startup developing AI-powered tools to create and edit synthetic voices, is making its Reader app available across the world with support for 32 languages.

The app, first released in June in the U.S., the U.K. and Canada, lets users upload any text content — like articles, PDF documents or e-books — and listen to it in different languages and voices. Reader now supports languages including Portuguese, Spanish, French, Hindi, German, Japanese, Arabic, Korean, Italian, Tamil and Swedish.

ElevenLabs, which became a  unicorn earlier this year after raising $80 million  from investors, including Andreessen Horowitz, provides an API that companies can use for various use cases like dubbing or text-to-speech. The company powers voice interactions on the Rabbit r1 , as well as text-to-speech features on AI-powered search engine Perplexity and audio platforms Pocket FM and Kuku FM . The Reader app is its first consumer-facing product.

The startup said it has added hundreds of new voices from its library that are suited for different languages. Last month, the company licensed the voices of actors such as Judy Garland, James Dean, Burt Reynolds and Sir Laurence Olivier for the app.

ElevenLabs said the extended language support is powered by its Turbo v2.5 model, released last month , which purportedly reduces the latency of text-to-speech conversion and improves quality.

The Reader app’s closest rival is Speechify , which offers additional features like scanning documents for text, integrations with Gmail and Canvas, as well as letting users clone their own voice to read out text. Mozilla-owned Pocket and The New York Times’ Audm-based audio app also let users listen to content.

ElevenLabs said it would add more features to the app, such as offline support and the ability to share audio snippets.

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