sami7777
fa0628f0e2
- slices.py: extract overlapping audio chunks for manual review (filename embeds start/end timestamps for easy reference) - speech_regions.py: find/extract only the speech regions (silence stripping), useful as a faster-whisper pre-processing step - waveform.py: fix silencedetect verbosity (info, not error) + regex parser to handle '[silencedetect @ 0x...] silence_start: 0' prefix - cli.py: new 'slices' subcommand - tests: 12 new tests (slices, speech_regions, regex); 61 total all passing - README: updated with subcommand table + step-by-step workflow
119 lines
4.3 KiB
Markdown
119 lines
4.3 KiB
Markdown
# sermon-clean
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A one-shot CLI for sermon audio editing: **find** bad segments, **cut** them out, **paste** in ElevenLabs replacements. Built because doing this by hand every time is unbearable.
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## Why
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Recording a sermon is fine. Post-production is not. The current workflow needs:
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1. Manually identify where the bad words are (the painful part — Whisper stalls on long audio, and eyeballing a waveform is imprecise)
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2. Hand-write ffmpeg trim commands for each bad window
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3. Render replacement clips via ElevenLabs
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4. Hand-write the ffmpeg concat command
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5. Manually upload to Dropbox
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`sermon-clean` collapses steps 1-5 into one command (or a few, if you want to eyeball the audio first).
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## Install
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```bash
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# Requires ffmpeg in PATH (sudo apt install ffmpeg on Debian/Ubuntu)
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pip install sermon-clean
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# Optional: for ElevenLabs auto-rendering
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export ELEVENLABS_API_KEY=...
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export ELEVENLABS_VOICE_ID=IYUnpZr9CQfSylOsOOBo # your cloned voice
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# Optional: for auto-detect mode (transcribe + find bad words)
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pip install "sermon-clean[auto]"
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```
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## Usage
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### One-shot: explicit timestamps + replacement text
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```bash
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sermon-clean pipe sermon.ogg \
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--bad "21:38-21:42:the actual sentence you meant to say" \
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--bad "1450.3-1453.1:the corrected phrase" \
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--elevenlabs-text \
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-o sermon-fixed.ogg
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```
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### Step-by-step workflow
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```bash
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# 1. Look at the audio — see its shape + find silence gaps
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sermon-clean scan sermon.ogg --width 100
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# 2. Or: extract overlapping slices for manual review
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sermon-clean slices sermon.ogg --output-dir ./slices \
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--slice-seconds 5 --overlap-seconds 1
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# Listen to ./slices/slice_000_0-00-0-05.ogg in your audio player.
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# Filename embeds start/end timestamps.
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# 3. Edit the JSON to mark bad segments + replacement text:
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# segs.json:
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# [
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# {"start": 1298.0, "end": 1302.0, "reason": "misspoke", "replacement_text": "the actual sentence"},
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# {"start": 1450.3, "end": 1453.1, "reason": "misspoke", "replacement_text": "the corrected phrase"}
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# ]
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# 4. Trim the original around the bad windows
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sermon-clean cut sermon.ogg --segments-file segs.json
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# 5. Render replacements (if you haven't already) and splice
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sermon-clean paste sermon.ogg --segments-file segs.json \
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--replacements "replacements/*.mp3" \
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-o sermon-fixed.ogg
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```
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### Auto-detect mode (optional, requires `faster-whisper`)
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```bash
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sermon-clean auto sermon.ogg --bad-words "fuck,shit,damn" --output segs.json
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# transcribes the audio, finds timestamps for any of the bad words,
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# prints a suggested JSON file you can edit before splicing
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```
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## Subcommands
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| Command | Purpose |
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|---|---|
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| `find` | Show audio metadata + silence gaps (no transcription) |
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| `scan` | ASCII waveform + silence marks (no transcription) |
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| `slices` | Extract overlapping audio chunks for manual review |
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| `cut` | Trim the original around bad windows (no splice) |
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| `paste` | Splice pre-rendered replacements into the trimmed original |
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| `auto` | Transcribe + find bad-word timestamps |
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| `pipe` | Run cut + paste in one command |
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## How it works
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- **Find** → `ffmpeg silencedetect` for natural breath pauses, plus your explicit timestamps
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- **Cut** → trim the original into N+1 good segments using ffmpeg, re-encoding to the source codec (no `wav` intermediate — bitrate-matched)
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- **Paste** → ElevenLabs renders + ffmpeg concat with bit-exact `-c copy` (no audible clicks at splice boundaries)
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- **Verify** → ffprobe the output duration against expected; if it drifted >1s, the splice silently changed the runtime
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## Why this exists
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The previous workflow (`audio-splice-workflow.md` in krystie-profile) was a 5-step manual recipe that's already broken twice. Each fix took 30+ minutes of bash. This package makes the same workflow a one-line command.
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## Performance
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- `scan` on a 27-min audio: ~50s (Opus decode is the bottleneck on this CPU)
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- `slices` on a 27-min audio with 5-sec slices: ~50s
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- `auto` on a 27-min audio: ~10-20 min with `tiny.en` model on CPU. Use `base.en` or `small.en` for better accuracy at 2-4x the time. Whisper `tiny.en` is the right model for finding a known bad-word list — you don't need higher accuracy than "did the word 'fuck' appear at all."
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## Development
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```bash
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git clone https://git.sami/sami7777/sermon-clean.git
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cd sermon-clean
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pip install -e ".[test,auto]"
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pytest # 61 tests, ~17s
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```
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## License
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MIT — see LICENSE. |