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# Producer
Local speech cleanup and mastering for voice recordings. Noise removal uses `DeepFilterNet3`. Filtering, dynamics and loudness normalization are `FFmpeg`.
`producer.sh` bootstraps its own managed Python environments and downloads
dependencies and models automatically.
## Requirements
- glibc
- `uv` (or Python 3)
- NVidia driver and toolkit (optional)
## Usage
```bash
git clone https://git.historia.vg/git/producer
./producer.sh setup
./producer.sh recording.wav
```
First run installs the runtime into `lib/runtime/` and may take a few minutes.
The `process` keyword is optional; `./producer.sh process recording.wav` is
equivalent.
The master WAV is always **mono, 32-bit PCM**, at 48 kHz (default) or 44.1
kHz; stereo inputs must be downmixed to mono first. MP3 is encoded as
constant bitrate at 192 kb/s by default. Loudness is normalized to **-19
LUFS with a -1.5 dBTP true-peak ceiling**.
### Examples
```
# Optional MP3 alongside the WAV
./producer.sh recording.wav --mp3
# Other sound profiles
./producer.sh recording.wav --profile narrator
./producer.sh recording.wav --profile radio
# Process several files at once
./producer.sh take1.wav take2.wav --mp3
# Write outputs somewhere else
./producer.sh recording.wav --output-dir delivery --mp3
# Skip AI noise removal (FFT fallback or none at all)
./producer.sh recording.wav --denoiser fft
./producer.sh recording.wav --no-denoise
# Use the ClearVoice MossFormer2_SE_48K denoiser instead of DeepFilterNet3
# (larger download; preserves word attacks noticeably better at high strength)
./producer.sh recording.wav --denoiser clearvoice
./producer.sh setup --denoiser clearvoice --device cpu
# Shorten long gaps between takes (speech is never attenuated)
./producer.sh recording.wav --trim-silence --max-gap-s 1.5 --gap-pad-s 0.6
# LibriVox-style delivery file: 44.1 kHz, 128 kbps CBR, -19 LUFS, mono
./producer.sh recording.wav \
--sample-rate 44100 --mp3 --mp3-bitrate 128 \
--target-lufs -19 --true-peak-db -1.5
```
Edit default settings in `config.toml`
## Profiles
| Profile | Sound |
| -------------- | --------------------------------------------------------- |
| `natural` | Mild EQ, 2:1 compression, light de-essing (default) |
| `narrator` | Gentler compression, slower attack, wider loudness range |
| `radio` | Stronger compression, more warmth/presence, tighter range |
| `cleanup-only` | Denoise + highpass only; no EQ, dynamics or normalization |
AI denoisers soften word attacks to some degree; `clearvoice`
(MossFormer2_SE_48K) was measured to leave onsets essentially untouched,
while `deepfilter` ducks them a couple of percent even at reduced strength.
Denoisers also never reach true digital silence: a noise floor remains in
blank sections. `--trim-silence` addresses both properly - long gaps are
shortened to `--gap-pad-s` of untouched room tone with a sample-exact cut,
so speech is never gated or attenuated.
Test the difference on your own audio before committing:
```bash
./producer.sh preview recording.wav --start 10 --duration 30
```
## Troubleshooting
- **Bootstrap fails:** the first run needs `uv` or Python 3 with venv support
and network access to PyPI. Install the missing tool and rerun.
- **CUDA unavailable:** run `./producer.sh doctor`, check `nvidia-smi` and the
driver, then retry `./producer.sh setup --device cuda`. Or use `--device cpu`.
- **Sounds watery or thin:** lower the denoise strength (`--denoise-strength
0.65`) or compare profiles with `preview`.
- **Word attacks sound soft or ramp up:** AI denoisers can soften consonant
onsets. Try `--denoiser clearvoice` (larger non-causal model that sees more
attack context), lower `--denoise-strength`, or compare against
`--no-denoise` to locate the culprit.
## License
[0BSD](LICENSE).
Upstream components (DeepFilterNet, PyTorch, FFmpeg, uv)
carry their own licenses
|
