OpenAI Whisper Batch Transcription Pipeline

Processes audio files from an S3 bucket using Whisper large-v3, splitting recordings into 30-second chunks with ffmpeg before transcription. Outputs timestamped SRT and VTT subtitle files plus plain-text transcripts, then uploads artifacts back to S3. Supports language auto-detection and translation to English.

Installation

Use the upstream install or setup path that matches your environment:

• pip install -U openai-whisper
• pip install git+https://github.com/openai/whisper.git
• pip install --upgrade --no-deps --force-reinstall git+https://github.com/openai/whisper.git
• brew install ffmpeg

Requirements and caveats from upstream:

• We used Python 3.9.9 and PyTorch 1.10.1 to train and test our models, but the codebase is expected to be compatible with Python 3.8-3.11 and recent PyTorch versions. The codebase also depends o...
• Alternatively, the following command will pull and install the latest commit from this repository, along with its Python dependencies:
• It also requires the command-line tool ffmpeg to be installed on your system, which is available from most package managers:

Basic usage or getting-started notes:

• [Colab example]

• To update the package to the latest version of this repository, please run:

• bash

• Source: https://github.com/openai/whisper

• Extracted from upstream docs: https://raw.githubusercontent.com/openai/whisper/HEAD/README.md

Source

• Agent Skill Exchange