Skip to main content

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

Project description

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+. 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).

Usage

  • Start interactive recording and transcribe:
    • s2t
  • Short options:
    • Language: -l de (long: --lang de)
    • Model: -m large-v3 (long: --model large-v3)
    • 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

  • Für Entwickler-Setup und Beitragshinweise siehe CONTRIBUTING.md.
  • Für den Release-Prozess siehe docs/RELEASING.md.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

s2t-0.1.7.tar.gz (30.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

s2t-0.1.7-py3-none-any.whl (24.0 kB view details)

Uploaded Python 3

File details

Details for the file s2t-0.1.7.tar.gz.

File metadata

  • Download URL: s2t-0.1.7.tar.gz
  • Upload date:
  • Size: 30.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.8

File hashes

Hashes for s2t-0.1.7.tar.gz
Algorithm Hash digest
SHA256 bf270df90479463c6a7e78a757a01c90f4187cb8d3c22e03d813772cdfb6cec4
MD5 3ee4d69e5cafe34de4ef5a8f3aa5b24c
BLAKE2b-256 d39237eb8713314c855f10eed220cd8c0a8782a538196d1a27d4004f1ddfa9b3

See more details on using hashes here.

File details

Details for the file s2t-0.1.7-py3-none-any.whl.

File metadata

  • Download URL: s2t-0.1.7-py3-none-any.whl
  • Upload date:
  • Size: 24.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.8

File hashes

Hashes for s2t-0.1.7-py3-none-any.whl
Algorithm Hash digest
SHA256 e0012dac053d20b1c475f060bdc33a037991b904488f6f42312851822cc9eaee
MD5 b929e582bb371d35703c73926bf1e6f3
BLAKE2b-256 3ea78901a06fd07536e5f4b211c72a39db84868df34ca62845ea0de7af7e2952

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page