Hindi_ASR

Hindi_ASR

A Gradio app that turns spoken Hindi into text with the anuragshas wav2vec2 XLS-R model. It suits people who want to transcribe Hindi audio in a browser.

Made by anuragshas 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: Hindi_ASR is a Gradio app on Hugging Face Spaces for automatic speech recognition in Hindi. Its settings name a Hindi wav2vec2 XLS-R 1B checkpoint from the author anuragshas. The repository includes one sample audio file and a list of system packages.

Who it suits: It suits people who want to turn Hindi speech into text in a browser, and developers who want a short example of a speech model behind a Gradio page.

Industry | Who uses it | How they use it | Example
Media | Transcribers | Get a first draft of a Hindi recording | Open the Space and upload an audio clip
Education | Language learners | Check how well a model hears spoken Hindi | Speak a sentence and read the text
Software | Python developers | Read app.py to see how the speech model is called | Download the Space and open app.py

Anyone who needs other languages or documented accuracy can skip it, since the source gives neither.

Where to use it:

• A web browser, straight from the Space page on Hugging Face
• Windows, macOS or Linux with Python, as a local copy

Use case | Who | What they get back
Transcribe Hindi audio | Transcribers | The recognised text shown in the browser
Study a speech demo | Learners | An app file, package lists and one sample audio file

How to set it up: Using it online needs nothing. A local copy needs these first.

• Python and pip
• The huggingface_hub package, to fetch the files
• The packages in requirements.txt, plus Gradio
• The system packages in packages.txt, which Hugging Face installs with apt-get

1. Install the Hugging Face Hub package.
2. Download the Space into a folder called Hindi_ASR.
3. Move into that folder.
4. Install Gradio, then the packages from requirements.txt.
5. Start the app.

pip install -U huggingface_hub
hf download anuragshas/Hindi_ASR --repo-type space --local-dir Hindi_ASR
cd Hindi_ASR
pip install gradio
pip install -r requirements.txt
python app.py

How to use it: Open the Space page on Hugging Face, give it Hindi audio and read the text it returns. For a local copy, run python app.py in the folder and open the page it starts.

Example: You open the Space page and play the sample audio file through the app. The speech model listens to it and shows the Hindi text it recognises.

For newcomers and experts: If you are new, try the sample audio first. Speech recognition means a program listens to a recording and writes down what was said.

If you know the field, the named checkpoint is a wav2vec2 XLS-R 1B model fine-tuned for Hindi, and its name says it uses a language model. Accuracy and training data are not given in the source.

You give the app Hindi audio
The wav2vec2 model listens to the speech
The recognised text shows on the page

Good to know:

• The README gives no description, so settings and limits are clear only from the page and the code
• It needs Gradio, the packages in requirements.txt and the system packages in packages.txt
• License: apache-2
• Cost to run: none named
• Data it reaches: the audio you give it and the model it names

On Hugging Face, 13 November 2026

• Likes: 1
• Built with: gradio
• License: apache-2.0

Links

• Space: https://huggingface.co/spaces/anuragshas/Hindi_ASR
• Files: https://huggingface.co/spaces/anuragshas/Hindi_ASR/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.