# Show HN: CrispVoice – Studio voice enhancement that never uploads your voice

> Source: <https://github.com/Francium-Tech/CrispVoice>
> Published: 2026-07-26 13:25:30+00:00

**Studio-quality voice enhancement that never uploads your voice.**

Live demo with before/after audio: [crispvoice.francium.tech](https://crispvoice.francium.tech)

Take any voice recording - a phone memo, a laptop-mic capture, a noisy call - and get back clean, full-bodied, podcast-ready audio. Runs 100% locally: your audio never leaves your machine.

Inspired by the excellent [cleanvoice.ai](https://cleanvoice.ai/) and tools
like Adobe Podcast Enhance. They showed what is possible; this project open
sources *how* it is done, for anyone who wants the same result without
sending their voice to a server.

"Studio quality" is two problems, and this pipeline solves both:

**Restoration**- a generative model ([Resemble Enhance](https://github.com/resemble-ai/resemble-enhance), MIT) re-synthesizes the voice at 44.1 kHz, removing noise and adding back the bandwidth and body a cheap microphone never captured.**Texture blend**- 25% of a[DeepFilterNet](https://github.com/Rikorose/DeepFilterNet)-denoised copy of the original is mixed back in. Re-synthesis alone sounds subtly synthetic; the blend restores the natural transients, breaths, and room decay of the real recording. This stage came out of blind A/B testing against a commercial reference and moved the quality from "processed" to "studio."**Mastering**- a broadcast-style ffmpeg chain: chest warmth, articulation and air EQ, de-essing, gentle 2:1 compression, and EBU R128 loudness normalization to -19 LUFS.

See [ARCHITECTURE.md](/Francium-Tech/CrispVoice/blob/main/ARCHITECTURE.md) for the full technical breakdown,
including how the mastering EQ was fitted band-by-band against a commercial
tool's output.

Two short clips, before and after (or use the players on the
[demo page](https://crispvoice.francium.tech)):

| Voice | Before | After |
|---|---|---|
| Interview, room noise |
|

[demo/crispvoice.mp3](/Francium-Tech/CrispVoice/blob/main/demo/crispvoice.mp3)[demo/woman.m4a](/Francium-Tech/CrispVoice/blob/main/demo/woman.m4a)[demo/woman_crispvoice.mp3](/Francium-Tech/CrispVoice/blob/main/demo/woman_crispvoice.mp3)Requires [uv](https://docs.astral.sh/uv/) and curl. Tested on macOS
(Apple Silicon); Linux x86_64 should work. ~4 GB disk total.

```
git clone https://github.com/Francium-Tech/CrispVoice.git
cd CrispVoice
./setup.sh                    # one-time: local Python + PyTorch + model weights
./enhance recording.mp3       # writes recording_studio.wav
```

More options:

```
./enhance in.mp3 out.mp3          # output format follows the extension (wav/mp3/m4a)
./enhance in.mp3 --preview 30     # quick sample: process only the first 30 seconds
./enhance in.mp3 --nfe 32         # ~2x faster, slightly lower quality (default 64)
./enhance in.mp3 --blend 0.4      # more natural texture (default 0.25)
./enhance in.mp3 --preset natural # lighter compression, more dynamics
./enhance in.mp3 --denoise-only   # cleanup without generative re-synthesis
./enhance in.mp3 --threads 2      # use even less CPU
./enhance in.mp3 --no-master      # skip the mastering chain
```

Progress, ETA, and memory usage are printed for every chunk.

**Private by default.** No network calls after setup. Ever.**Self-contained.** The Python interpreter, PyTorch, model weights, and even the ffmpeg binary all live inside the project folder. Nothing is installed system-wide.`./uninstall.sh`

removes every trace in one go.**Never hog the machine.** CPU-only (deliberately: on Apple Silicon the GPU shares unified memory with the OS, and PyTorch's MPS backend can exhaust it and freeze the machine - a lesson learned the hard way). Half the cores, low process priority, bounded memory via 10-second chunks. Throughput is roughly 2.5x real time on an M-series CPU: an 8-minute recording takes about 20 minutes. (Speed was traded for quality; lower`--nfe`

if you want it faster.)

[Resemble AI](https://github.com/resemble-ai/resemble-enhance)for the MIT-licensed enhancement model that does the heavy lifting.[cleanvoice.ai](https://cleanvoice.ai/)for the inspiration and the quality bar to chase.[FFmpeg](https://ffmpeg.org/)for decoding, mastering, and encoding.

CrispVoice is an open source project by [Francium Tech](https://francium.tech).

MIT. Model weights are downloaded separately from
[ResembleAI/resemble-enhance](https://huggingface.co/ResembleAI/resemble-enhance)
(also MIT) and are not part of this repository.