This is a simple web application that allows users to transcribe audio files into text using the Whisper Automatic Speech Recognition (ASR) model. The application is built using Streamlit and leverages OpenAI's Whisper to perform transcriptions.
- Upload Audio: Click on the button and select (or drag and drop) an audio file in WAV, MP3, or M4A format that you want to transcribe.
- Transcribe Audio: Once the audio file is uploaded, click on the "Transcribe Audio" button in the sidebar. The application will start transcribing the audio using the Whisper model.
- Supported Languages: The Whisper model supports multiple languages. The application will automatically detect the language of the uploaded audio and provide accurate transcriptions for a wide range of languages. This includes Afrikaans, Arabic, Armenian, Azerbaijani, Belarusian, Bosnian, Bulgarian, Catalan, Chinese, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, Galician, German, Greek, Hebrew, Hindi, Hungarian, Icelandic, Indonesian, Italian, Japanese, Kannada, Kazakh, Korean, Latvian, Lithuanian, Macedonian, Malay, Marathi, Maori, Nepali, Norwegian, Persian, Polish, Portuguese, Romanian, Russian, Serbian, Slovak, Slovenian, Spanish, Swahili, Swedish, Tagalog, Tamil, Thai, Turkish, Ukrainian, Urdu, Vietnamese, and Welsh.
- Clean-up: After the transcription is complete, the temporary audio file will be removed to ensure your data privacy.
To run this application locally, you need to have Python installed along with the following packages:
- Streamlit
- Whisper
- Torch
You can install the required packages using the following commands:
pip install streamlit
pip install openai-whisper
pip install torch
pip install torchaudio
pip install torchvision
- Clone this repository to your local machine.
- Open a terminal or command prompt and navigate to the repository's directory.
- Run the Streamlit application:
streamlit run whisper-app.py - The application will open in your web browser, and you can start transcribing audio files right away.