speech to text bot

The best speech-to-text Discord bot!

Have a deaf/HoH friend? Want to be able to moderate voice chats as easily as text chats? No matter your reason, Scripty comes to the rescue! Set it up once and forget about it forever. The bot will sit quietly and transcribe all of your conversations without having to do anything else. For free. Forever.

Why Scripty?

It's open source., it's multilingual., it's easy to use., it's private., convinced yet, scripty's features, transcriptions, voice assistant (coming soon), voice chat moderation, text to speech (coming soon), custom voice (coming soon, premium only), complete privacy, still not convinced.

Why not take a look at our comparison with the only other known transcription bot out there?

Got questions?

We've got the answers. Join our Discord server to ask any question you might have about Scripty, to make sure it's the right fit for your server. (Hint: it is)

You knew it was coming. We don't like making people pay for this. Go check out our Premium tiers at the button below. Help support us in our mission to create a completely free, completely private, open-source transcription bot for Discord.

Important Links

Speech to Text - Voice Typing & Transcription

Take notes with your voice for free, or automatically transcribe audio & video recordings. amazingly accurate, secure & blazing fast..

~ Proudly serving millions of users since 2015 ~

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Dictate Notes

Start taking notes, on our online voice-enabled notepad right away, for free. Learn more.

Transcribe Recordings

Automatically transcribe (& optionally translate) recordings, audio and video files, YouTubes and more, in no time. Learn more.

Speechnotes is a reliable and secure web-based speech-to-text tool that enables you to quickly and accurately transcribe & translate your audio and video recordings, as well as dictate your notes instead of typing, saving you time and effort. With features like voice commands for punctuation and formatting, automatic capitalization, and easy import/export options, Speechnotes provides an efficient and user-friendly dictation and transcription experience. Proudly serving millions of users since 2015, Speechnotes is the go-to tool for anyone who needs fast, accurate & private transcription. Our Portfolio of Complementary Speech-To-Text Tools Includes:

Voice typing - Chrome extension

Dictate instead of typing on any form & text-box across the web. Including on Gmail, and more.

Transcription API & webhooks

Speechnotes' API enables you to send us files via standard POST requests, and get the transcription results sent directly to your server.

Zapier integration

Combine the power of automatic transcriptions with Zapier's automatic processes. Serverless & codeless automation! Connect with your CRM, phone calls, Docs, email & more.

Android Speechnotes app

Speechnotes' notepad for Android, for notes taking on your mobile, battle tested with more than 5Million downloads. Rated 4.3+ ⭐

iOS TextHear app

TextHear for iOS, works great on iPhones, iPads & Macs. Designed specifically to help people with hearing impairment participate in conversations. Please note, this is a sister app - so it has its own pricing plan.

Audio & video converting tools

Tools developed for fast - batch conversions of audio files from one type to another and extracting audio only from videos for minimizing uploads.

Our Sister Apps for Text-To-Speech & Live Captioning

Complementary to Speechnotes

Reads out loud texts, files & web pages

Listen on the go to any written content, from custom texts to websites & e-books, for free.

Speechlogger

Live Captioning & Translation

Live captions & simultaneous translation for conferences, online meetings, webinars & more.

Need Human Transcription? We Can Offer a 10% Discount Coupon

We do not provide human transcription services ourselves, but, we partnered with a UK company that does. Learn more on human transcription and the 10% discount .

Dictation Notepad

Start taking notes with your voice for free

Speech to Text online notepad. Professional, accurate & free speech recognizing text editor. Distraction-free, fast, easy to use web app for dictation & typing.

Speechnotes is a powerful speech-enabled online notepad, designed to empower your ideas by implementing a clean & efficient design, so you can focus on your thoughts. We strive to provide the best online dictation tool by engaging cutting-edge speech-recognition technology for the most accurate results technology can achieve today, together with incorporating built-in tools (automatic or manual) to increase users' efficiency, productivity and comfort. Works entirely online in your Chrome browser. No download, no install and even no registration needed, so you can start working right away.

Speechnotes is especially designed to provide you a distraction-free environment. Every note, starts with a new clear white paper, so to stimulate your mind with a clean fresh start. All other elements but the text itself are out of sight by fading out, so you can concentrate on the most important part - your own creativity. In addition to that, speaking instead of typing, enables you to think and speak it out fluently, uninterrupted, which again encourages creative, clear thinking. Fonts and colors all over the app were designed to be sharp and have excellent legibility characteristics.

Example use cases

• Voice typing
• Writing notes, thoughts
• Medical forms - dictate
• Transcribers (listen and dictate)

Transcription Service

Start transcribing

Fast turnaround - results within minutes. Includes timestamps, auto punctuation and subtitles at unbeatable price. Protects your privacy: no human in the loop, and (unlike many other vendors) we do NOT keep your audio. Pay per use, no recurring payments. Upload your files or transcribe directly from Google Drive, YouTube or any other online source. Simple. No download or install. Just send us the file and get the results in minutes.

• Transcribe interviews
• Captions for Youtubes & movies
• Auto-transcribe phone calls or voice messages
• Students - transcribe lectures
• Podcasters - enlarge your audience by turning your podcasts into textual content
• Text-index entire audio archives

Key Advantages

Speechnotes is powered by the leading most accurate speech recognition AI engines by Google & Microsoft. We always check - and make sure we still use the best. Accuracy in English is very good and can easily reach 95% accuracy for good quality dictation or recording.

Lightweight & fast

Both Speechnotes dictation & transcription are lightweight-online no install, work out of the box anywhere you are. Dictation works in real time. Transcription will get you results in a matter of minutes.

Super Private & Secure!

Super private - no human handles, sees or listens to your recordings! In addition, we take great measures to protect your privacy. For example, for transcribing your recordings - we pay Google's speech to text engines extra - just so they do not keep your audio for their own research purposes.

Health advantages

Typing may result in different types of Computer Related Repetitive Strain Injuries (RSI). Voice typing is one of the main recommended ways to minimize these risks, as it enables you to sit back comfortably, freeing your arms, hands, shoulders and back altogether.

Saves you time

Need to transcribe a recording? If it's an hour long, transcribing it yourself will take you about 6! hours of work. If you send it to a transcriber - you will get it back in days! Upload it to Speechnotes - it will take you less than a minute, and you will get the results in about 20 minutes to your email.

Saves you money

Speechnotes dictation notepad is completely free - with ads - or a small fee to get it ad-free. Speechnotes transcription is only $0.1/minute, which is X10 times cheaper than a human transcriber! We offer the best deal on the market - whether it's the free dictation notepad ot the pay-as-you-go transcription service.

Dictation - Free

• Online dictation notepad
• Voice typing Chrome extension

Dictation - Premium

• Premium online dictation notepad
• Premium voice typing Chrome extension
• Support from the development team

Transcription

$0.1 /minute.

• Pay as you go - no subscription
• Audio & video recordings
• Speaker diarization in English
• Generate captions .srt files
• REST API, webhooks & Zapier integration

Compare plans

Privacy Policy

We at Speechnotes, Speechlogger, TextHear, Speechkeys value your privacy, and that's why we do not store anything you say or type or in fact any other data about you - unless it is solely needed for the purpose of your operation. We don't share it with 3rd parties, other than Google / Microsoft for the speech-to-text engine.

Privacy - how are the recordings and results handled?

- transcription service.

Our transcription service is probably the most private and secure transcription service available.

• HIPAA compliant.
• No human in the loop. No passing your recording between PCs, emails, employees, etc.
• Secure encrypted communications (https) with and between our servers.
• Recordings are automatically deleted from our servers as soon as the transcription is done.
• Our contract with Google / Microsoft (our speech engines providers) prohibits them from keeping any audio or results.
• Transcription results are securely kept on our secure database. Only you have access to them - only if you sign in (or provide your secret credentials through the API)
• You may choose to delete the transcription results - once you do - no copy remains on our servers.

- Dictation notepad & extension

For dictation, the recording & recognition - is delegated to and done by the browser (Chrome / Edge) or operating system (Android). So, we never even have access to the recorded audio, and Edge's / Chrome's / Android's (depending the one you use) privacy policy apply here.

The results of the dictation are saved locally on your machine - via the browser's / app's local storage. It never gets to our servers. So, as long as your device is private - your notes are private.

Payments method privacy

The whole payments process is delegated to PayPal / Stripe / Google Pay / Play Store / App Store and secured by these providers. We never receive any of your credit card information.

More generic notes regarding our site, cookies, analytics, ads, etc.

• We may use Google Analytics on our site - which is a generic tool to track usage statistics.
• We use cookies - which means we save data on your browser to send to our servers when needed. This is used for instance to sign you in, and then keep you signed in.
• For the dictation tool - we use your browser's local storage to store your notes, so you can access them later.
• Non premium dictation tool serves ads by Google. Users may opt out of personalized advertising by visiting Ads Settings . Alternatively, users can opt out of a third-party vendor's use of cookies for personalized advertising by visiting https://youradchoices.com/
• In case you would like to upload files to Google Drive directly from Speechnotes - we'll ask for your permission to do so. We will use that permission for that purpose only - syncing your speech-notes to your Google Drive, per your request.

Breaking The Communication Gap

Scriptly is changing the way people from around the world communicate on Discord. It provides immersive features such as audio transcription (/transcribe), and text to speech (/tts), easing communication for everyone.

Speech-To-Text (/transcribe)

• Get a text based version of what users say!
• Transcribe meetings in voice channels and get a real time text output in a Discord text channel!
• Includes the ability to also transcribe voice messages through the message context menu.
• Useful for individuals who are hard-of-hearing (HOH), deaf, or have other auditory processing difficulties.
• Privacy preserving with no logging and foundational features free forever!
• Continuously improving with modes specific to speed and accuracy.
• AKA: closed-captions, speech recognition, voice-to-text, voice transcription, dictation, and audio-to-text.

Text-To-Speech (/tts)

• Speak your message in a voice channel clearly and efficiently!
• Includes a total of 300+ high-quality text-to-speech voices with premium!
• Unlimited text-to-speech message length for all users!
• Customize by setting a text-to-speech channel for messages to be automatically read from and more!
• Useful for no-mic channels, and individuals who are mute or are otherwise unable to speak in voice channels.
• AKA: voice synthesis, read-aloud, no mic, voiceover, speech-generation, and computer-generated speech.

Text-to-Speech

Bring your chatbot to a whole new level: give it a voice

Chatbots that can speak, thanks to our free text-to-speech technology

Your chatbot should always have a personality, a style of speech that reflects its purpose. Not only because this is more engaging for the user, but also because there is a significant marketing message in the vocabulary and manner of speech of your chatbot. Just think about the difference between the kind of tone you want to strike if your bot is working for a bank (reliable, wise and sombre) or a thrash metal band (lively, youthful and energetic).

FREE CONVERSATIONAL SOFTWARE

Well, on the SnatchBot platform a whole new level of engagement experience is possible with the world’s first free talking chatbots. We have made text-to-speech available in over sixty languages and, in the English language, you can choose from ten voices: five male, five female. Each voice has a short sample for you to listen to as you create and edit your chatbot, so you can choose the most appropriate tone before you switch on text-to-speech.

Make Your Online Chatbot More Accessible

By giving your users the option of listening to the chatbot, rather than reading, you are achieving two important goals. Firstly, making it easier for them to access the conversation and secondly, you are giving them a much more entertaining and engaging quality of experience.

This functionality is particularly valuable in terms of accessibility. Visually impaired users, for example, will welcome the option of listening to the chatbot’s responses, rather than having to read them. And there are always going to be situations where users, whether VI or not, will prefer to listen to a chatbot’s response than read it.

Text-to-Speech in Action

The Text to Speech service understands text and natural language to generate synthesized audio output complete with appropriate cadence and intonation. It is available in 60 languages .

Test our Text to Speech in action by replacing the below content by the one you wish to hear. The text language must match the selected voice language. Possibilities are endless.

THE BEST CHATBOT PLATFORM

On our roadmap is the opposite functionality, speech-to-text, or speech recognition. Our goal is to provide you with the most amazing chatbot experience. And for now, this functionality, unique to SnatchBot is incredibly easy to deploy on dozens of channels, including Skype, Telegram, LINE Messenger, Slack, Viber and more.

Here’s how you add a voice to your chatbot . Enjoy!

SPEECHTEXT .AI

Ai-powered transcription chatbot, turn audio and video content to text and subtitles in minutes.

How It Works

Transcriber bot quickly and accurately converts audio or video files into text and subtitles!

Upload audio/video files or share public weblinks (e.g. shared Google Drive or Dropbox files, YouTube, Vimeo, Dailymotion, TikTok, Facebook, Instagram, Twitch videos, and more) with Transcriber bot.

The transcription process usually takes half of the audio file length to transcribe a file completely. Transcriber bot will notify you when the transcription results are ready.

Edit and Export

Transcriber bot connects your audio to the text in the online proofreading editor. It will help you quickly verify and export transcription results to TXT, DOCX, XLSX, PDF, RTF, ODT, HTML, SRT, VTT.

Set of amazing features to help you transcribe audio and video in seconds

Speech recognition

Powerful speech-to-text technology automatically converts voice to text in seconds

Multi language

Audio to text transcription software supports multiple languages

Speaker Identification

Service detects which individuals spoke which words in multi-participant conversations

Transcribe Anywhere

Transcribe local files or files accessible over public URLs (Google Drive, Dropbox, YouTube, Vimeo, etc.)

Automatic Punctuation

Audio and video transcriptions include commas, full stops, question marks, periods

Editing Tools

Proofreading interface helps users to edit and verify speech recognition results

Export Transcript

Export audio transcription results in the format of your choice (txt, pdf, docx, etc.)

Frequently Asked Questions

Transcriber bot is fully GDPR compliant. All our physical servers are located in Europe (France) and we encrypt all your data sent between you and the service. The transcription service is fully automated, hence your data is confidential and the process has no place for human-factor and other risks that manual transcription has. You can delete transcription results and uploaded files at any time. Data security at Slack and Google Chat is the highest priority. You can read more about their security and compliance practices here: Slack , Google Chat .

Transcriber bot currently supports English, German, French, Spanish, Dutch, Italian, Portuguese, Russian, Chinese, Japanese, Korean, Arabic, Hindi, Polish, Swedish, Norwegian, Danish, Finnish, Turkish, Romanian, Czech, Ukrainian, Greek, Thai, Indonesian, Vietnamese, Filipino languages. If you need another language, please use our transcription platform .

You can try Transcriber bot for free. 30 minutes of transcription included for all new accounts. If you need more, please refer to our pricing page .

We provide a set of pay-as-you-go packages. A pay-as-you-go system is one in which you pay for the service before you use it and you cannot use more than you have paid for. All our prepaid packages are lifetime offers without monthly charges. If you have used up the minutes purchased you can upgrade your account again to the select prepaid package.

We accept PayPal, Amazon Pay, and all major credit cards (including Visa, Mastercard, Discover, American Express, and UnionPay).

Yes, we do. Contact our team if you transcribe over 500 hours per year and they can assist you.

Yes. Order receipt email messages sent to customers include a link to the customer's Account Management site where you can download your invoices.

We do not store or collect your payment card details. That information is provided directly to our third-party payment processor. The payment processor adheres to the standards set by PCI-DSS as managed by the PCI Security Standards Council, which is a joint effort of brands like Visa, Mastercard, American Express, and Discover. PCI-DSS requirements help ensure the secure handling of payment information.

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Create a new medium for engagement with AI narrations by making every article available in audio

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FutureSmart AI Blog

Building a Conversational Voice Chatbot: Integrating OpenAI's Speech-to-Text & Text-to-Speech

Table of contents

Introduction, 1. install required libraries, 2. set up the .env file, 3. understanding the project structure, streamlit interface setup, handling voice inputs, chatbot response processing, speech_to_text function, text_to_speech function, get_answer function, chatbot interaction flow, additional resources.

Welcome to an engaging tutorial where we'll develop a voice-responsive chatbot utilizing OpenAI's advanced speech-to-text and text-to-speech services, all integrated within a Streamlit web application. This project is not just about textual interactions; it's about enabling a natural, voice-based dialogue with a chatbot.

For those who might not be familiar with OpenAI's capabilities in handling speech, I recommend watching my detailed video ( watch here ). It provides an excellent introduction to the speech-to-text and text-to-speech functionalities that are central to our project.

In this blog, we will walk through the entire process of setting up the development environment, incorporating OpenAI services into our application, and crafting a chatbot that can seamlessly converse with users using voice inputs and outputs.

Setting Up the Environment

To begin building our voice-responsive OpenAI chatbot, it's essential to set up the right development environment. This involves installing necessary libraries and configuring API access. Here's how you can get started:

Your chatbot relies on several Python libraries, as listed in the requirements.txt file. These libraries include Streamlit for the web interface, OpenAI for accessing speech processing services, and others for specific functionalities like audio recording. Install them by running the following command in your project directory:

Here's a quick breakdown of the key libraries:

streamlit : For building and running the web app.

openai : To access OpenAI's API for speech-to-text and text-to-speech services.

audio_recorder_streamlit : To record audio within the Streamlit app.

streamlit-float : Provides floating elements in the Streamlit interface.

Sensitive information such as your OpenAI API key should be stored in a .env file. This approach keeps your credentials secure. Create a .env file in the root of your project and include your OpenAI API key like this:

Ensure that this file is not shared publicly, especially if you are pushing your code to a public repository.

Your project primarily consists of two Python files:

app.py : This file contains the Streamlit web application logic. It's where you define the user interface and manage the flow of input/output for the chatbot.

utils.py : This file includes functions for processing speech-to-text and text-to-speech, as well as generating chatbot responses.

With your environment set up and a basic understanding of your project's structure, you're now ready to start building the chatbot's functionalities.

Building the Chatbot: Streamlit Interface ( app.py )

In this section, we dive into the construction of our chatbot, focusing on how the Streamlit interface is set up and how voice inputs are handled and processed in app.py .

Streamlit is a powerful tool that allows us to quickly build interactive web applications for our chatbot. In app.py , the Streamlit application is initialized and configured to handle user interactions:

In this setup, we initialize the Streamlit app, import necessary functions from utils.py , and set up the session state to track and manage chat messages. The float_init() function from streamlit_float is used to create floating elements, enhancing the user interface.

The core functionality of our chatbot is its ability to handle voice inputs. This is achieved using the audio_recorder_streamlit library, which allows us to record audio directly in the Streamlit interface:

The audio_recorder() function captures audio input from the user. Once the audio is recorded, it's processed to extract the spoken text:

Here, we write the recorded audio to a file and then use the speech_to_text function from utils.py to convert it into text. The transcribed text is then added to the session state for the chatbot to process.

Once a user's voice input is converted to text, the chatbot processes this input to generate a response:

In this part of the code, the get_answer function is used to generate a text response based on the user's input. This response is then converted to speech using the text_to_speech function, and the audio is played back to the user.

Integrating OpenAI's Services ( utils.py )

In utils.py , we have defined key functions that integrate OpenAI's speech-to-text and text-to-speech services, along with the logic for generating chatbot responses. Let's explore these functions in detail.

The speech_to_text function is responsible for converting the audio input from the user into text. This is a critical step in enabling the chatbot to understand and process user queries:

In this function, the audio file captured from the user is opened and sent to OpenAI's speech-to-text service. The service transcribes the audio into text using the Whisper model, which is known for its high accuracy in speech recognition. The transcribed text is then returned for further processing by the chatbot.

Conversely, the text_to_speech function takes the chatbot's textual response and converts it into an audio format, allowing the chatbot to 'speak' back to the user:

Here, the chatbot's response text is converted into speech using OpenAI's text-to-speech service. The output is saved as an audio file, which is then played back to the user, creating an audio response.

The get_answer function generates the chatbot's responses to user inputs. It uses OpenAI's language models to create contextually appropriate and conversational replies:

In this function, the conversation history is combined with a system message defining the chatbot's role. This data is then sent to OpenAI's conversational AI model, which generates a response based on the input and context.

The interaction flow of the chatbot, as orchestrated in app.py , is a seamless integration of these functionalities. When a user speaks to the chatbot, the audio is recorded and converted to text using speech_to_text . The chatbot then processes this input with get_answer to generate a response. Finally, this response is converted back into speech using text_to_speech , allowing the chatbot to audibly communicate with the user. This flow creates a natural and interactive conversational experience, showcasing the potential of integrating advanced AI and speech processing technologies in a user-friendly application.

As we wrap up our exploration of building a voice-responsive OpenAI chatbot with Streamlit, let's reflect on what we've accomplished and the potential for further development.

Reflecting on the Project

This project demonstrates the power and versatility of integrating advanced AI services into a user-friendly application. By combining OpenAI's speech-to-text and text-to-speech capabilities with Streamlit, we've created a chatbot that can understand spoken language and respond in kind. The key functionalities we've implemented, such as handling voice inputs, generating intelligent responses, and speaking back to the user, exemplify how AI can be used to create more natural and engaging user interfaces.

For a detailed walkthrough of this project and a practical demonstration, make sure to watch my YouTube video . Also, you can access the complete code and documentation on my GitHub repository .

If you're curious about the latest in AI technology, I invite you to visit my project, AI Demos, at aidemos.com . It's a rich resource offering a wide array of video demos showcasing the most advanced AI tools. My goal with AI Demos is to educate and illuminate the diverse possibilities of AI.

For even more in-depth exploration, be sure to visit my YouTube channel at youtube.com/@aidemos.futuresmart . Here, you'll find a wealth of content that delves into the exciting future of AI and its various applications.

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Speaker.bot

Supercharged Text to Speech (TTS) for your live stream!

Supported Speech Engines

Use your favorite TTS engine with Speaker.bot

Google Cloud

Convert text into natural-sounding speech using an API powered by the best of Google’s AI technologies.

Engage global audiences by using 400 neural voices across 140 languages and variants available with Azure TTS

Amazon Polly

Deploy high-quality, natural-sounding human voices in dozens of languages

IBM Watson Text to Speech API

Microsoft Speech API (SAPI), the native speech API for Windows.

The Open Source Voice AI Community

TTS Monster

Custom AI Text to Speech for Streamers

Text to Speech solutions by Acapela Group

Text to Speech by CereProc

Eleven Labs

Text to Speech by ElevenLabs.io

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Discord Speech-To-Text bot in Python using Google Cloud Speech-To-Text API

vadimkantorov/discordspeechtotext

Folders and files.

Repository files navigation

How to create and configure a discord bot.

https://medium.com/voice-tech-podcast/how-to-make-a-discord-bot-with-python-e066b03bfd9

Installation

Unfortunately, discord.py does not support yet receiving voice (as opposed to discord.js ). In the meanwhile I use @imayhaveborkedit's excellent fork . Hopefully, the changes will get merged upstream: Rapptz/discord.py#1094 , Rapptz/discord.py#444

• Python 100.0%

Voice   Generator

This web app allows you to generate voice audio from text - no login needed, and it's completely free! It uses your browser's built-in voice synthesis technology, and so the voices will differ depending on the browser that you're using. You can download the audio as a file, but note that the downloaded voices may be different to your browser's voices because they are downloaded from an external text-to-speech server. If you don't like the externally-downloaded voice, you can use a recording app on your device to record the "system" or "internal" sound while you're playing the generated voice audio.

Want more voices? You can download the generated audio and then use voicechanger.io to add effects to the voice. For example, you can make the voice sound more robotic, or like a giant ogre, or an evil demon. You can even use it to reverse the generated audio, randomly distort the speed of the voice throughout the audio, add a scary ghost effect, or add an "anonymous hacker" effect to it.

Note: If the list of available text-to-speech voices is small, or all the voices sound the same, then you may need to install text-to-speech voices on your device. Many operating systems (including some versions of Android, for example) only come with one voice by default, and the others need to be downloaded in your device's settings. If you don't know how to install more voices, and you can't find a tutorial online, you can try downloading the audio with the download button instead. As mentioned above, the downloaded audio uses external voices which may be different to your device's local ones.

You're free to use the generated voices for any purpose - no attribution needed. You could use this website as a free voice over generator for narrating your videos in cases where don't want to use your real voice. You can also adjust the pitch of the voice to make it sound younger/older, and you can even adjust the rate/speed of the generated speech, so you can create a fast-talking high-pitched chipmunk voice if you want to.

Note: If you have offline-compatible voices installed on your device (check your system Text-To-Speech settings), then this web app works offline! Find the "add to homescreen" or "install" button in your browser to add a shortcut to this app in your home screen. And note that if you don't have an internet connection, or if for some reason the voice audio download isn't working for you, you can also use a recording app that records your devices "internal" or "system" sound.

Got some feedback? You can share it with me here .

If you like this project check out these: AI Chat , AI Anime Generator , AI Image Generator , and AI Story Generator .

Discord text to speech bot

• over 100 voices
• language transalation
• multiple users can use it as one
• remembers your settings

Add to discord Try me

India Is Emerging as a Key Player in the Global AI Race

A s Asia’s richest man, Mukesh Ambani, addressed his shareholders during a much-anticipated yearly address last Thursday, he also unveiled “JioBrain,” a suite of artificial intelligence (AI) tools and applications that he says will transform a spate of businesses in energy, textiles, telecommunications and more that form his multinational conglomerate, Reliance Industries. “By perfecting JioBrain within Reliance, we will create a powerful AI service platform that we can offer to other enterprises as well,” Ambani said during his speech.

The Reliance Chairman’s latest offering comes as India emerges as a crucial player in the global AI ecosystem, boasting a high-powered IT industry worth $250 billion, which serves many of the world’s banks, manufacturers and firms. As the world’s most populous country, India also has a robust workforce population with nearly 5 million programmers at a time when AI talent is in short supply globally, with analysts predicting that India’s AI services could be worth $17 billion by 2027, according to a recent report by Nasscom and BCG.

Puneet Chandok, the President of Microsoft India & South Asia, points to research that finds India has one of the highest AI adoption rates among knowledge workers, with 92% using generative AI at work—significantly higher than the global average of 75%. “These insights highlight the significant impact of AI on the Indian workforce and the proactive steps being taken by both employees and leaders to integrate AI into their daily routines,” Chandok says, adding that the company is also powering initiatives that aim to equip 2 million people with AI skills by 2025.

The spotlight on India comes at a time when many countries around the globe are keen to foster their own competing AI systems rather than turning to the U.S. or China. In the last few years, the Indian government has nurtured an ecosystem where global players like Google and Meta, Indian businesses like Reliance Jio and Tata Consulting Services, and homegrown startups can take advantage of its cost-efficient technological landscape.

India’s “bottom-up” approach to AI

India also aspires to have what Rajeev Chandrasekhar, the former Indian Minister for Electronics and Information Technology, calls “sovereign AI,” by integrating large-scale models across sectors like healthcare, agriculture, and governance to drive economic growth. In March, the government ramped up investment worth $1.25 billion towards an ambitious “IndiaAI Mission,” which will aid the development of computing infrastructure, startups and the use of AI applications in the public sector.

“Interestingly, the government itself is the main driver behind India’s AI transformation,” says Jibu Elias, a leading AI researcher and ethicist who helped create IndiaAI. Elias says the push has accelerated since 2020. “We want India to be like a global garage for AI tools, especially for the Global South.”

“The idea is that if you can build tools that address some of the decade-long socio-economic challenges in India, they can be adopted across the globe,” he continues.

It’s a method that Arvind Gupta, who heads the Digital India Foundation in New Delhi, calls a “bottom-up” approach: “Unlike the Googles and Microsofts of the world, India took it to the next level by building trust in technology with digital public infrastructure,” he says. Digital public infrastructure, also known as DPI, is a public-private partnership that was introduced by the government nearly a decade ago by combining technology, governance and civil society. It extends to a biometric identification system, a fast payments system, and consent-based data sharing that now gives India’s 1.4 billion citizens access to public services. 

Gupta says DPI is instrumental in giving India an advantage in the global AI race. With 900 million Indians connected to the internet, he points to India being “the data capital of the world,” which has “leapfrogged into the whole culture of artificial intelligence.” That’s because much of this data exists in public data sets that companies can use to write their own AI algorithm. “You won’t see that anywhere else in the world,” Gupta says.

The race to build LLMs as chipmakers eye Indian market

With so much data publicly available, a swath of Indian startups are now racing to build their own large language models or LLMs, which harness generative AI by learning from vast quantities of data. And in a country where people speak more than a dozen languages, “India's diverse and multilingual environment makes it an ideal test bed for developing and refining global AI solutions,” says Chandok from Microsoft. 

In January, Krutrim, an AI startup founded by entrepreneur Bhavish Aggarwal whose name translators to “artificial” in Sanskrit, became India’s first unicorn when it secured $50 million in funding from prominent Silicon Valley investors like Lightspeed Venture Partners and billionaire Vinod Khosla. Similarly, Bengaluru-based startup Sarvam recently launched a voice-enabled AI bot that supports more than 10 Indian languages using open-source software after raising $41 million. The government is also supplementing this innovation by building “targeted LLMs” that can do real-time language translation for citizens accessing public services, Gupta adds.

Still, India’s AI push can’t accelerate without computing power and shared resources. To address this gap, last month, the Indian government finalized the procurement of a thousand graphics processing units, or GPUs, to offer computing capacity to AI makers. Last September, the CEO of chipmaker Nvidia, Jensen Huang, visited India to sit down with Modi and tech executives, setting the company’s sights on the country as a potential location for chip production as the U.S. increasingly clamps down on the export of high-end chips from China. “You have the data, you have the talent,” Huang told Modi at the time. “This is going to be one of the largest AI markets in the world.” This March, the first consignment of Nvidia chips arrived in Indian data centers after the company forged a partnership with Indian cloud services company Yotta, powering its Shakti Cloud as India’s fastest AI supercomputing infrastructure. 

Against this backdrop, billionaire-owned Indian companies are eager not to be left behind. In July, India's largest software company, Tata Consultancy Services (TCS), heavily invested in a generative AI project pipeline exceeding $1.5 billion. Gautam Adani, Asia’s second-richest person, announced a joint venture with UAE in December to explore AI and diversify into digital services. 

And as for Ambani, who has urged his employees to accelerate AI transformation across all businesses this year, the goal is clear: “We need to be at the forefront of using data, with AI as an enabler for achieving a quantum jump in productivity and efficiency,” the billionaire told Reliance employees. 

Since then, Jio, Reliance’s telecommunications business, has worked with the Indian Institute of Technology to launch “Bharat GPT,” a ChatGPT-style service for Indian users. A video played during a Reliance event demonstrated how the speech-to-text tool would work if successful: a motorcycle mechanic speaks to the AI bot in his native Tamil, a banker uses the tool in Hindi, and a developer in Hyderabad writes computer code in Telegu.

“It’s like the Indian joint family,” said Ganesh Ramakrishnan, the chair of IIT Bombay’s computer science and engineering department. “We are interdependent, and we do better together.”

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Write to Astha Rajvanshi at [email protected]

Using Generative AI Models in Circuit Design

Generative models have been making big waves in the past few years, from intelligent text-generating large language models (LLMs) to creative image and video-generation models. At NVIDIA, we are exploring using generative AI models to speed up the circuit design process and deliver better designs to meet the ever-increasing demands for computational power.

Circuit design is a challenging optimization problem. Designers often need to balance several conflicting objectives, such as power and area, and satisfy constraints, such as hitting a specific timing. The design space is usually combinatorial, making it difficult to find optimal designs. Previous research into prefix circuit design used hand-crafted heuristics and reinforcement learning to explore the vast design space. For more details, see Towards Optimal Performance-Area Trade-Off in Adders by Synthesis of Parallel Prefix Structures and Cross-Layer Optimization for High Speed Adders: A Pareto Driven Machine Learning Approach .

While these methods help to overcome the vastness of the search space, they are associated with high computational costs to train and often have poor generalizability. 

Our paper CircuitVAE: Efficient and Scalable Latent Circuit Optimization , recently published at the Design Automation Conference, provides a glimpse into the potential of generative models in circuit designs. We demonstrate that variational autoencoders (VAEs), a class of generative models, can produce better prefix adder designs at a fraction of the computational cost required by previous approaches.

The complexity of circuit design

In our paper, we focus on optimizing prefix adders, a class of circuits prevalent in modern GPUs. We represent a prefix adder with a tree, as shown in Figure 1. We minimize two metrics, area and delay, which we combine using a weighted sum into a single objective. 

What are variational autoencoders?

VAEs are generative models that estimate some data distribution. We can sample from the estimated distribution after training a VAE model. VAEs are versatile in modeling data of different modalities, from images to graphs. A VAE model consists of an encoder and a decoder. 

In the case of image generation, an encoder maps an input image to a distribution of vectors called a latent space. A decoder converts the vector of an encoded image back to an image. The VAE is trained by minimizing the reconstruction loss between inputs and outputs, along with a regularization loss on the latent space. VAEs are generative models because they can generate new outputs by sampling vectors from the latent space and decoding them with the learned decoder.

CircuitVAE: VAE for circuit design

CircuitVAE is a search algorithm that embeds computation graphs in a continuous space and optimizes a learned surrogate of physical simulation by gradient descent. It learns to embed circuits into a continuous latent space and predict quality metrics, such as area and delay, from latent representations. The cost predictor is fully differentiable when it is instantiated with a neural network. Thus, it’s possible to apply gradient descent in the latent space to optimize circuit metrics, circumventing the challenge of searching in a combinatorial design space.

CircuitVAE training

The CircuitVAE training loss has two parts: 

• The standard VAE reconstruction and regularization losses.
• The mean squared error between the true and the predicted area and delay produced by the cost predictor model using the encoded circuit latent vectors. 

While fitting the cost predictor, the latent space is organized according to costs, which is amenable to gradient-based optimization. A set of adders is generated through the genetic algorithm to bootstrap the training. One could also use a random sample of adders to start.

Gradient-based optimization

After training a CircuitVAE model, it’s used to find prefix tree structures that minimize costs. First choose a latent vector using cost-weighted sampling, a technique that ensures starting from a good design. This vector is then modified with gradient descent by minimizing the cost estimated by the cost predictor model. The final vector is decoded into a prefix tree and synthesized to obtain its actual cost.

The full CircuitVAE algorithm interleaves the training and optimization stage. After each round of model training, more data is collected with gradient-based optimization and physical synthesis. Model fitting resumes with a growing dataset of circuits and associated metrics, resulting in a virtuous cycle where the cost predictor model increases in accuracy, leading to a more targeted optimization.

We tested our approach on the design of circuits that have 32 inputs and 64 inputs (the width of the prefix tree circuit, corresponding to 32 bits and 64 bits). To supply our physical synthesis with components needed for simulation, we used an open-source cell library called Nangate45.

Figure 4 shows the cost progression while each method evaluates more designs through physical simulations. CircuitVAE consistently achieves the lowest costs compared to baseline methods. Both RL and GA optimize in the discrete domain and are slow to explore, while CircuitVAE is 2-3x faster, thanks to gradient-based optimization in the latent space.

We evaluated CircuitVAE in a real-world prefix adder task with a proprietary cell library with input-output timings captured from a complete datapath. Figure 5 shows that CircuitVAE generates designs that form a better Pareto frontier of area and delay than a commercial tool. 

CircuitVAE showcases the power of generative models in circuit design tasks. Operating in a latent space, rather than the combinatorially large discrete space of circuit designs, reaps the benefits of continuous optimization in the form of reduced computational costs. We believe this transformation from discrete to continuous holds promise in other areas of hardware design, such as place-and-route. We anticipate that generative models will play an increasingly central role in hardware design.

For more information about CircuitVAE, see CircuitVAE: Efficient and Scalable Latent Circuit Optimization .

Related resources

• GTC session: Generative AI Theater: Supercharge Semiconductor Design With Generative AI: How NVIDIA Chip Designers Use Large Language Models (LLMs) to Increase Productivity
• GTC session: A New Era of AI-Driven Electronic Design Automation on Accelerated Computing
• GTC session: What’s Next in Generative AI
• Webinar: Building Generative AI Applications for Enterprise Demands
• Webinar: What AI Teams Need to Know About Generative AI
• Webinar: Fast-Track to Generative AI With NVIDIA

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