s2t 0.1.17

Speech to Text (s2t): Record audio, run Whisper, export formats, and copy transcript to clipboard.

s2t

Record audio from your microphone, run Whisper to transcribe it, export common formats, and copy the .txt transcript to your clipboard.

Install

• From local checkout:
  • Editable: pip install -e .
  • Standard: pip install .

Requirements: Python 3.11–3.12. No mandatory external binaries. ffmpeg is optional (only for MP3 encoding/decoding).

System requirements (Linux)

• Some environments need system libraries for audio I/O:
  • Debian/Ubuntu: sudo apt-get install libportaudio2 libsndfile1
  • Fedora/RHEL: sudo dnf install portaudio libsndfile
• Optional for MP3: ffmpeg (sudo apt-get install ffmpeg or brew install ffmpeg).
• Optional backends:
  • faster-whisper (CTranslate2): pip install faster-whisper (GPU via CUDA on NVIDIA; CPU works well with int8).
  • whisper.cpp (Metal/CPU): pip install whispercpp (requires local gguf models; experimental GPU on Apple varies by build).

Usage

• Start interactive recording and transcribe:
  • s2t
• Short options:
  • Language: -l de (long: --lang de)
  • Model: -m large-v3 (long: --model large-v3)
  • Backend: --backend whisper|faster|whispercpp (default: whisper)
  • Device: --device auto|cpu|cuda|mps (default: auto)
  • Sample rate: -r 48000 (long: --rate 48000)
  • Channels: -c 2 (long: --channels 2)
  • Output dir: -o transcripts (long: --outdir transcripts) — default is transcripts/ if omitted
  • Translate to English: -t (long: --translate). You may still provide --lang as an input-language hint if you want.
  • List available models and exit: -L (long: --list-models)
  • Recording format: -f flac|wav|mp3 (long: --recording-format), default flac. MP3 requires ffmpeg; if absent, it falls back to FLAC with a warning.
  • Auto-split on silence: --silence-sec 1.0 (default 1.0; 0 disables). When continuous silence ≥ this many seconds is detected, the current chunk is ended automatically.
  • Minimum chunk length for auto-split: --min-chunk-sec 5.0 (default 5.0). Prevents very short chunks and avoids splitting early in a sentence.
  • Prompt mode (spoken prompt): -p (long: --prompt). Speak your prompt first, then press SPACE to use it as prompt and continue with your main content. If you press ENTER instead of SPACE, no prompt is used; the spoken audio is transcribed as normal payload and the session ends.
  • Keep chunk files: --keep-chunks — by default, per‑chunk audio and per‑chunk Whisper outputs are deleted after the final merge.
  • Open transcript for editing: -e (long: --edit) — opens the generated .txt in your shell editor ($VISUAL/$EDITOR).
• Examples:
  • Transcribe in German using large-v3: s2t -l de -m large-v3
  • Translate any input to English: s2t -t
  • Write outputs under transcripts/: s2t -o transcripts
  • List local model names: s2t -L

Outputs are written into a timestamped folder under the chosen output directory (default is transcripts/), e.g. transcripts/2025-01-31T14-22-05+0200/, containing:

• Per‑chunk outputs: chunk_####.flac/.wav plus chunk_####.txt/.srt/.vtt/.tsv/.json (deleted by default unless --keep-chunks)
• Final outputs: recording.flac/.wav (and recording.mp3 if requested and ffmpeg available), plus recording.txt/.srt/.vtt/.tsv/.json
• Clipboard mirrors the combined .txt with blank lines between chunks.

Auto-splitting details

• SPACE always splits immediately; ENTER finishes the recording.
• With --silence-sec > 0, chunks end automatically after detected continuous silence of that many seconds.
• Auto-split only triggers once the current chunk has at least --min-chunk-sec seconds and after speech has been detected (to ignore leading silence). A short internal cooldown avoids duplicate splits.

Makefile (optional)

• Setup venv + dev deps: make setup
• Lint/format/test: make lint, make format, make test; combined gate: make check
• Build sdist/wheel: make build (runs check first)
• Publish to PyPI/TestPyPI: make publish, make publish-test (run after build)
• Run CLI: make record ARGS='-l de -t -o transcripts'
• List models: make list-models
• Show package version: make version

Notes on models

• The local openai-whisper CLI supports models like: tiny, base, small, medium, large-v1, large-v2, large-v3 and their .en variants.
• The name turbo refers to OpenAI’s hosted model family and is not provided by the local whisper CLI. If you pass -m turbo, the command may fail; choose a supported local model instead.

Development & Release

• For developer setup and contribution guidelines, see CONTRIBUTING.md.
• For the release process, see docs/RELEASING.md.