polyvoice

Speaker diarization for Rust — who spoke when, on CPU, without Python.

Beta-quality, ONNX-powered, ~30 MB. Embeds into any Rust app, with Python, C, and CLI bindings.

Speaker_0: 0.0s - 12.3s
Speaker_1: 14.1s - 28.7s
Speaker_0: 31.2s - 45.0s

Like-for-like (collar 0, overlap-scored) VoxConverse-test DER is 18.5% vs pyannote 3.1's 11.3% — a few DER points traded for a CPU-only, MIT, ungated engine that needs no Python — see Benchmarks.

Install

cargo add polyvoice --features "onnx,download"   # Rust library
pip install polyvoice                             # Python
cargo install polyvoice --features cli            # CLI

Usage

use polyvoice::models::ModelRegistry;
use polyvoice::pipeline_v2::Pipeline;
use polyvoice::types::{Profile, SampleRate};

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let pipeline = Pipeline::builder()
        .profile(Profile::Balanced)                  // auto speaker count
        .with_models_from(ModelRegistry::default()?) // models auto-download on first run
        .build()?;

    let (samples, sr) = polyvoice::wav::read_wav("meeting.wav")?;
    let result = pipeline.run(&samples, SampleRate::new(sr).ok_or("bad sample rate")?)?;

    for turn in &result.turns {
        println!("{}: {:.1}s - {:.1}s", turn.speaker, turn.time.start, turn.time.end);
    }
    Ok(())
}

polyvoice download-models --profile balanced
polyvoice diarize meeting.wav --output meeting.rttm

Python usage and the full API live on docs.rs.

Why polyvoice

• Maintained, pure-Rust, streaming-capable. The popular sherpa-rs bindings are archived; polyvoice is an actively-maintained, pure-Rust diarization path (ONNX via ort, no C++ toolkit) with first-class streaming.
• One library, four surfaces. Rust + Python + C FFI + CLI from a single crate.
• CPU-first, ~30 MB, MIT. No GPU, no Python runtime, no gated model access.

It is not the accuracy leader — like-for-like (collar 0, overlap-scored) VoxConverse-test DER is 18.5% versus 11.3% for pyannote 3.1. It trades those DER points for deployability: a pure-Rust, CPU, MIT, ungated engine (pyannote's weights are gated behind an HF token) with four bindings and streaming.

How it works

audio (f32 PCM)
  → VAD / Powerset segmentation
  → WeSpeaker embeddings
  → clustering (AHC / K-means / NME-SC, automatic speaker count)
  → speaker turns

Streaming (OnlineDiarizer) and batch (OfflineDiarizer), with a single-speaker guard so quiet or single-voice audio does not hallucinate clusters.

Documentation

• Benchmarks — collar-disclosed DER numbers and provenance
• Production readiness — deployment guidance (GO / NO-GO)
• Migrating from 0.5 · Glossary
• Contributing · Changelog

License

MIT

---

Name: this project is polyvoice — speaker diarization for Rust, unrelated to ByteDance's "PolyVoice" speech-translation research.