liquidinvestigations/openai-whisper-gradio repository overview

⁠Fork of https://github.com/innovatorved/whisper-openai-gradio-implementation⁠

Changes made:

• update to python 3.11 and gradio 3.32 (latest)
• disable telemetry and sharing
• download "large" model in docker container
• print .srt instead of .text

Original readme below.

⁠Whisper OpenAi Tool Gradio Web implementation

Whisper is an automatic speech recognition (ASR) system Gradio Web UI Implementation

⁠Installation

Install ffmeg on Your Device

  # on Ubuntu or Debian
  sudo apt update
  sudo apt install ffmpeg

  # on MacOS using Homebrew (https://brew.sh/)
  brew install ffmpeg

  # on Windows using Chocolatey (https://chocolatey.org/)
  choco install ffmpeg

  # on Windows using Scoop (https://scoop.sh/)
  scoop install ffmpeg

Download Program

  mkdir whisper-sppech2txt
  cd whisper-sppech2txt
  git clone https://github.com/innovatorved/whisper-openai-gradio-implementation.git .
  pip install -r requirements.txt

Run Program

  python app.py

⁠Available models and languages (Credit⁠)

There are five model sizes, four with English-only versions, offering speed and accuracy tradeoffs. Below are the names of the available models and their approximate memory requirements and relative speed.

For English-only applications, the .en models tend to perform better, especially for the tiny.en and base.en models. We observed that the difference becomes less significant for the small.en and medium.en models.

⁠Screenshots

⁠License

MIT⁠

⁠Reference

• https://github.com/openai/whisper⁠

• https://openai.com/blog/whisper/⁠

⁠Authors

• Ved Gupta⁠

⁠🚀 About Me

I'm a Developer i will feel the code then write .

⁠Support

For support, email [email protected]⁠