Transly

Transly is a web-based application that allows users to transcribe audio and video files using OpenAI's Whisper ASR model. The application provides a user-friendly interface for uploading files, selecting language and model options, and generating transcriptions.

Features

• Transcribe audio and video files to text.
• Choose from different language and model options.
• User-friendly web interface.

DEMO

Producing transcriptions for a segment from the Lex Freedman podcast featuring Elon Musk discussing the electricity crisis: https://www.youtube.com/watch?v=VRJmqJqPH80&t=41s

Installation

1. Clone the repository:

   git clone https://github.com/HarshitVashisht11/Web-Transcriber.git
   
   

2. Install Flask:

   pip install flask
   
   

3. Install PyTorch:

   pip install torch
   
   

4. Install Whisper:

    pip install -U openai-whisper
   
   

5. it also requires the command-line tool ffmpeg to be installed on your system, which is available from most package managers:

   # on Ubuntu or Debian
   sudo apt update && sudo apt install ffmpeg
   
   # on Arch Linux
   sudo pacman -S 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
   
   

Using GPU

The Web Transcriber supports GPU acceleration for faster transcription. Ensure that you have a compatible GPU and the necessary GPU drivers installed. The application uses the GPU to enhance the speed of the transcription process.

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 inference speed relative to the large model; actual speed may vary depending on many factors including the available hardware.

Size	Parameters	English-only model	Multilingual model	Required VRAM	Relative speed
tiny	39 M	tiny.en	tiny	~1 GB	~32x
base	74 M	base.en	base	~1 GB	~16x
small	244 M	small.en	small	~2 GB	~6x
medium	769 M	medium.en	medium	~5 GB	~2x
large	1550 M	N/A	large	~10 GB	1x