README.md

---
title: Audio to Text
emoji: ▶︎ •၊၊||၊|။||||။‌‌‌‌‌၊|• 0:10 ➤ 📄

colorFrom: blue
colorTo: yellow
sdk: gradio
app_file: app.py
pinned: false
license: apache-2.0
---

# Whisper Small Model Demo

This Space demonstrates the capabilities of OpenAI's Whisper small model for automatic speech recognition (ASR). Users
can upload audio files or record audio directly to obtain transcriptions.

## Overview

Whisper is a state-of-the-art ASR model developed by OpenAI. This demo utilizes the small variant of Whisper to
transcribe spoken language into text. The application is built using [Gradio](https://gradio.app/), which provides an
intuitive web interface for machine learning models.

## Features

- **Audio Input**: Upload pre-recorded audio files or record audio in real-time.
- **Transcription**: Generate text transcriptions of the input audio.
- **Language Support**: Whisper supports multiple languages; however, this demo is optimized for English.

## Usage

1. **Select Input Method**:
    - *Upload*: Click on the "Upload" button to select an audio file from your device.
    - *Record*: Use the "Record" button to capture audio using your microphone.

2. **Transcription**:
    - After providing the audio input, click on the "Transcribe" button.
    - The transcription will appear in the output box below.

## Requirements

To run this demo locally, ensure you have the following installed:

- Python 3.8 or higher
- Required Python packages listed in `requirements.txt`

## Setup Instructions

1. **Clone the Repository**:

   ```bash
   git clone https://huggingface.co/spaces/your-username/whisper-small-demo
   cd whisper-small-demo
   ```

2. **Install Dependencies**:

   ```bash
   pip install -r requirements.txt
   ```

3. **Run the Application**:

   ```bash
   python app.py
   ```

   Access the demo locally at `http://localhost:7860`.

## Acknowledgements

- [OpenAI](https://openai.com/) for developing the Whisper model.
- [Gradio](https://gradio.app/) for providing an easy-to-use interface for machine learning applications.
- [Hugging Face Spaces](https://huggingface.co/spaces) for hosting this demo.

## References

- [OpenAI Whisper GitHub Repository](https://github.com/openai/whisper)
- [Gradio Documentation](https://gradio.app/docs/)
- [Hugging Face Spaces Documentation](https://huggingface.co/docs/hub/spaces)