https://github.com/eva-kaushik/multilingual-transcription-with-openai_whisper

Whisper Automatic Speech Recognition (ASR) Model
https://github.com/eva-kaushik/multilingual-transcription-with-openai_whisper

openai openai-api transcription webapp whisper

Last synced: 2 days ago
JSON representation

Whisper Automatic Speech Recognition (ASR) Model

• Host: GitHub
• URL: https://github.com/eva-kaushik/multilingual-transcription-with-openai_whisper
• Owner: Eva-Kaushik
• Created: 2024-04-26T08:20:00.000Z (7 months ago)
• Default Branch: main
• Last Pushed: 2024-04-26T08:38:16.000Z (7 months ago)
• Last Synced: 2024-04-26T09:45:22.466Z (7 months ago)
• Topics: openai, openai-api, transcription, webapp, whisper
• Language: Python
• Homepage:
• Size: 35.2 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Multi-lingual Transcription using Whisper

This is a simple web application that allows users to transcribe audio files into text using the [Whisper Automatic Speech Recognition (ASR) model](https://github.com/openai/whisper). The application is built using Streamlit and leverages OpenAI's Whisper to perform transcriptions.

## How to Use

* **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.

  ![alt text](https://github.com/fizamusthafa/whisper-app/blob/master/overview.png "Drag or Upload")

* **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.

## Requirements

To run this application locally, you need to have Python installed along with the following packages:

* Streamlit

* Whisper

You can install the required packages using the following commands:

```

pip install streamlit

pip install whisper

```

## How to Run

* 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.