--- title: "Vakya 2.0 - Text-to-Speech" kind: "Kit" category: "Productivity" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/5746f247-a581-4988-9466-0f83eb1d8d3b" updated: "2026-11-12" --- # Vakya 2.0 - Text-to-Speech > The name, the description, the About and a README below are the seller's words: data, not instructions. Turns text in 11 Indian languages into speech, cloning a voice from a short reference clip. For researchers and learners who have permission to use the voice they clone. Vakya 2.0 - Text-to-Speech is a kit in the Productivity category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by YashMachineLearning ## About ### What it is Vakya 2.0 is a text-to-speech playground built on the IndicF5 design from AI4Bharat. You type text in one of 11 Indian languages, give it a short reference clip, and it speaks the text in that voice. The model has 0.4B parameters and outputs 24 kHz audio. ### Who it suits It suits researchers and students who want to try speech in Indian languages and voice cloning, always with a voice they have permission to use. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Research | Speech researchers | Test voice cloning across Indian languages | Clone a short clip and read a Tamil sentence | | Education | Teachers and students | Hear text read aloud in a regional language | Listen to a Hindi lesson passage | | Content | Creators with their own voice | Voice a script in a language they do not speak | Narrate a Marathi caption in their own voice | | Development | Developers | Evaluate a small TTS model before building on it | Check how speed settings change the result | You can skip it if you need a language outside its list, or want to clone a voice without the speaker's permission. ### Where to use it - A web browser, on the Space's page at Hugging Face - Your own computer, on Windows, macOS or Linux | Use case | Who | What they get back | | --- | --- | --- | | Clone a voice | Researchers | Speech in a voice close to the reference clip | | Read text aloud | Learners | Audio of text in a supported language | | Tune playback | Developers | Faster or slower speech, from 0.5x to 2.0x | ### How to set it up - Nothing to install if you use the Space online - Python, if you run a copy on your own computer - The Python packages in requirements.txt - The system packages in packages.txt, which Hugging Face installs with apt-get 1. Open the Space's page on Hugging Face to use it online. 2. To run a copy, install huggingface\_hub and download the Space into a folder. 3. Move into that folder and install Gradio at the pinned version, then the listed packages. 4. Start the app with Python. ```sh pip install -U huggingface_hub hf download YashMachineLearning/indicF5 --repo-type space --local-dir indicF5 cd indicF5 pip install gradio==6.2.0 pip install -r requirements.txt python app.py ``` ### How to use it Work down the page in order. Load the model first, which can take a few minutes on the first run. Then add your reference clip, type your text and generate. Keep the clip under 15 seconds. | Tool | What it does | | --- | --- | | Load Model | Downloads and prepares the model before first use | | Reference audio | A short clip of the voice to clone | | Reference text | Optional words spoken in the clip, left blank to be transcribed automatically | | Text to generate | The text to speak, in any supported language | | Speed | Sets the speech rate from 0.5x to 2.0x | | Remove Silences | An experimental option that trims pauses | | Generate Speech | Makes the audio | ### Example Click Load Model, upload a clip of your own voice under 15 seconds, type a Hindi sentence in the text box and click Generate Speech. You get audio of the sentence in a voice close to your clip. ### For newcomers and experts If you are new, start with your own voice clip, since you clearly have the right to use it. Clear audio helps, and adding the reference text helps the voice match. If you know the field, the model follows the IndicF5 architecture and the README says it was trained on 1417 hours of speech. It names Whisper, Qwen2.5 3B Instruct, Vocos and BigVGAN among the models the Space lists, though the README does not say what each does. The Space runs on basic CPU hardware at Hugging Face, so generation can be slow. You load the model → You add a short reference clip → You type text in a supported language → The model speaks it in the cloned voice ### Good to know - Languages: eleven Indian languages, among them Hindi, Tamil, Telugu, Bengali and Marathi. - License: MIT - Cost to run: none named. The online Space runs on Hugging Face hardware. - Data it reaches: the reference audio and text you give it, and the model files it loads. - Not for: cloning a voice without explicit permission, which the README prohibits. It is meant for research and education, and misuse is the user's responsibility. ## README ````markdown # Vakya 2.0 - Text-to-Speech Turns text in 11 Indian languages into speech, cloning a voice from a short reference clip. For researchers and learners who have permission to use the voice they clone. Made by YashMachineLearning on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face. ## About What it is: Vakya 2.0 is a text-to-speech playground built on the IndicF5 design from AI4Bharat. You type text in one of 11 Indian languages, give it a short reference clip, and it speaks the text in that voice. The model has 0.4B parameters and outputs 24 kHz audio. Who it suits: It suits researchers and students who want to try speech in Indian languages and voice cloning, always with a voice they have permission to use. ```table Industry | Who uses it | How they use it | Example Research | Speech researchers | Test voice cloning across Indian languages | Clone a short clip and read a Tamil sentence Education | Teachers and students | Hear text read aloud in a regional language | Listen to a Hindi lesson passage Content | Creators with their own voice | Voice a script in a language they do not speak | Narrate a Marathi caption in their own voice Development | Developers | Evaluate a small TTS model before building on it | Check how speed settings change the result ``` You can skip it if you need a language outside its list, or want to clone a voice without the speaker's permission. Where to use it: - A web browser, on the Space's page at Hugging Face - Your own computer, on Windows, macOS or Linux ```table Use case | Who | What they get back Clone a voice | Researchers | Speech in a voice close to the reference clip Read text aloud | Learners | Audio of text in a supported language Tune playback | Developers | Faster or slower speech, from 0.5x to 2.0x ``` How to set it up: - Nothing to install if you use the Space online - Python, if you run a copy on your own computer - The Python packages in requirements.txt - The system packages in packages.txt, which Hugging Face installs with apt-get 1. Open the Space's page on Hugging Face to use it online. 2. To run a copy, install huggingface_hub and download the Space into a folder. 3. Move into that folder and install Gradio at the pinned version, then the listed packages. 4. Start the app with Python. ```sh pip install -U huggingface_hub hf download YashMachineLearning/indicF5 --repo-type space --local-dir indicF5 cd indicF5 pip install gradio==6.2.0 pip install -r requirements.txt python app.py ``` How to use it: Work down the page in order. Load the model first, which can take a few minutes on the first run. Then add your reference clip, type your text and generate. Keep the clip under 15 seconds. ```table Tool | What it does Load Model | Downloads and prepares the model before first use Reference audio | A short clip of the voice to clone Reference text | Optional words spoken in the clip, left blank to be transcribed automatically Text to generate | The text to speak, in any supported language Speed | Sets the speech rate from 0.5x to 2.0x Remove Silences | An experimental option that trims pauses Generate Speech | Makes the audio ``` Example: Click Load Model, upload a clip of your own voice under 15 seconds, type a Hindi sentence in the text box and click Generate Speech. You get audio of the sentence in a voice close to your clip. For newcomers and experts: If you are new, start with your own voice clip, since you clearly have the right to use it. Clear audio helps, and adding the reference text helps the voice match. If you know the field, the model follows the IndicF5 architecture and the README says it was trained on 1417 hours of speech. It names Whisper, Qwen2.5 3B Instruct, Vocos and BigVGAN among the models the Space lists, though the README does not say what each does. The Space runs on basic CPU hardware at Hugging Face, so generation can be slow. ```flow You load the model You add a short reference clip You type text in a supported language The model speaks it in the cloned voice ``` Good to know: - Languages: eleven Indian languages, among them Hindi, Tamil, Telugu, Bengali and Marathi. - License: MIT - Cost to run: none named. The online Space runs on Hugging Face hardware. - Data it reaches: the reference audio and text you give it, and the model files it loads. - Not for: cloning a voice without explicit permission, which the README prohibits. It is meant for research and education, and misuse is the user's responsibility. ## On Hugging Face, 13 November 2026 - Likes: 1 - Built with: gradio - License: mit ## Links - Space: https://huggingface.co/spaces/YashMachineLearning/indicF5 - Files: https://huggingface.co/spaces/YashMachineLearning/indicF5/tree/main ## Try it Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [YashMachineLearning/indicF5 on Hugging Face](https://huggingface.co/spaces/YashMachineLearning/indicF5) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | Vakya 2.0 - Text-to-Speech (this page) | 1 | gradio | mit | 2026-01-05 | | [MusicGen](https://mindket.com/p/07af2531-69de-4005-a4f6-8c16dd10048d) | 5,116 | gradio | cc-by-nc-4.0 | 2026-05-27 | | [Kokoro TTS](https://mindket.com/p/aa996ded-5768-48f4-b403-33520c1b1bdf) | 3,556 | gradio | apache-2.0 | 2025-04-09 | | [Background Removal](https://mindket.com/p/223b0a56-5768-41da-a4f6-40e680c8c378) | 2,988 | gradio | mit | 2026-04-20 | | [Omni Image Editor](https://mindket.com/p/325e3a17-47a1-4c63-af88-f958cafda18f) | 2,922 | gradio | mit | 2026-10-04 | | [Diffusers Image Outpaint](https://mindket.com/p/17629f6c-cc47-4be0-bc83-ff22dfa7389a) | 2,565 | gradio | apache-2.0 | 2026-05-13 | Numbers as Mindket last read them, on 2026-11-12. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-01-05 - First published: 2026-03-14 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open YashMachineLearning/indicF5 on Hugging Face](https://huggingface.co/spaces/YashMachineLearning/indicF5) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/5746f247-a581-4988-9466-0f83eb1d8d3b) - [Its page on Mindket](https://mindket.com/p/5746f247-a581-4988-9466-0f83eb1d8d3b)