/OpenAI_Whisper_Streamlit

A minimalistic automatic speech recognition streamlit based webapp powered by OpenAI's Whisper

Primary LanguagePythonMIT LicenseMIT

Automatic Speech Recognition using OpenAI's Whisper

A minimalistic automatic speech recognition streamlit based webapp powered by OpenAI's Whisper "State of the Art" models

Animation

Installation:

  • Simply run the command pip install -r requirements.txt to install the necessary dependencies.

Usage:

  1. Head over to this link and follow the steps to get a comprehensive overview of the architecture of OpenAI's whisper models.
  2. Simply run the command:
streamlit run app.py
  1. Navigate to http://localhost:8501 in your web-browser.
  2. By default, streamlit allows us to upload files of max. 200MB. If you want to have more size for uploading audio files, execute the command :
streamlit run app.py --server.maxUploadSize=1028

Running the Dockerized App

  1. Ensure you have Docker Installed and Setup in your OS (Windows/Mac/Linux). For detailed Instructions, please refer this.
  2. Navigate to the folder where you have cloned this repository ( where the Dockerfile is present ).
  3. Build the Docker Image (don't forget the dot!! 😄 ):
docker build -f Dockerfile -t app:latest .
  1. Run the docker:
docker run -p 8501:8501 app:latest

This will launch the dockerized app. Navigate to http://localhost:8501/ in your browser to have a look at your application. You can check the status of your all available running dockers by:

docker ps

Read more about Whisper here: https://lablab.ai/tech/whisper

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