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| 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) |