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Lightweight faster-whisper batch transcription CLI for researchers

Project description

whisper-wrap

Lightweight Python CLI wrapper around faster-whisper for bulk transcription.

Features

  • Batch transcribe audio/video files in a directory
  • Output formats: txt, srt, vtt, json
  • Always writes per-file output
  • Optional merged output via --merge
  • Metadata header included (file, duration if available, model, language, device, compute type)
  • Progress + summary + per-file errors

Install (uv)

uv sync

Run without installing globally:

uv run whisper-wrap --help

Usage

uv run whisper-wrap /path/to/media \
  --model small \
  --language en \
  --device cpu \
  --compute-type int8 \
  --threads 8 \
  --output-dir outputs \
  --format txt \
  --recursive \
  --ext mp3 --ext wav --ext mp4

Publish

cp .env.example .env
# add PYPI_API_TOKEN to .env
./scripts/publish.sh

Harvard sentences

uv run whisper-wrap harvard --format text
uv run whisper-wrap harvard --format json --limit 10

Attribution: Harvard Sentences (1965 revised list) from https://www.cs.columbia.edu/~hgs/audio/harvard.html (IEEE Transactions on Audio and Electroacoustics, Vol. 17, Issue 3, 1969).

Common flags

  • --model default: small
  • --language optional; omitted means auto-detect
  • --device one of cpu|cuda
  • --compute-type one of float16|int8
  • --threads CPU threads
  • --output-dir output folder
  • --merge also write a single merged.<format> file
  • --format one of txt|srt|vtt|json
  • --metadata/--no-metadata include metadata headers (default: on)
  • --ext repeatable extension filter (with or without .)
  • --recursive scan subdirectories

Notes

  • faster-whisper runtime behavior depends on local FFmpeg and model availability.
  • For cuda, ensure compatible CUDA runtime/drivers are installed.

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