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license: mit
base_model: onnx-community/pyannote-segmentation-3.0
pipeline_tag: voice-activity-detection
library_name: openasr
tags:
- speaker-diarization
- openasr
- oasr
---
<div align="center">
# pyannote Segmentation 3.0 · OpenASR
**pyannote segmentation-3.0 — speaker-change and overlap aware speech segmentation for OpenASR diarization**
[](https://huggingface.co/onnx-community/pyannote-segmentation-3.0)
[](https://github.com/QuintinShaw/openasr)
[](https://openasr.org)
[](https://huggingface.co/onnx-community/pyannote-segmentation-3.0)
Speaker-diarization support pack for the **[OpenASR](https://github.com/QuintinShaw/openasr)** runtime —
pure-Rust inference, **no Python at inference time**.
</div>
---
## ✨ Highlights
- ✂️ **Speaker-change aware segmentation** — PyanNet (SincNet + BiLSTM) with a powerset head that detects up to 3 concurrent speakers, including overlapped speech
- 🤝 **Quality upgrade for `--diarize`** — installed alongside the WeSpeaker embedder pack, it replaces coarse VAD slices with fine speaker-turn boundaries
- 🔒 **Diarization, not identification** — anonymous session-relative labels; nothing leaves the machine
- 🎯 **Bit-exact packaging** — single raw-f32 build; the pure-Rust forward pass matches the upstream ONNX logits (max abs error ~7e-5)
- 🦀 **Native in OpenASR** — `.oasr` packs run with no Python at inference, engineered for peak performance on CPU & GPU
## 🚀 Quickstart
```bash
# 1. Install the OpenASR CLI · https://openasr.org
# 2. Pull the pack
openasr pull pyannote-segmentation-3.0:f32
# 3. Diarize any transcription (works with every OpenASR ASR model)
openasr transcribe meeting.wav --model xasr-zh-en --diarize --format srt
```
## 📦 Pack
| Quant | File (`.oasr`) | Size |
|:------|:---------------|-----:|
| f32 | `pyannote-segmentation-3.0-f32.oasr` | 6 MB |
<sub>Single raw-**f32** build: the pure-Rust forward pass consumes f32 directly and the
parity gates assert bit-exact outputs vs the upstream weights, so no integer
quantization is produced.</sub>
## 🧠 About pyannote Segmentation 3.0
pyannote **segmentation-3.0** is the local speech-segmentation model from the pyannote speaker
diarization toolkit: a PyanNet (SincNet front-end + bidirectional LSTM) classifier over a 7-class
powerset that labels every 10 s window with which of up to three speakers are active — including
overlapped speech. OpenASR uses it as the optional segmentation stage of its model-agnostic
diarization pipeline: when this pack is installed, `--diarize` splits speech at speaker changes
instead of relying on coarse VAD slices, then the WeSpeaker embedder pack clusters the segments into
anonymous speaker turns. Weights are extracted from the un-gated, MIT-licensed
**onnx-community** ONNX mirror at a pinned revision and repackaged as a raw-f32 `.oasr` pack that
runs in pure Rust — no Python at inference time.
## ⚙️ How this pack was made
Converted from [onnx-community/pyannote-segmentation-3.0](https://huggingface.co/onnx-community/pyannote-segmentation-3.0) with the OpenASR importer:
```bash
openasr model-pack import pyannote <src>.safetensors <out>.oasr \
--package-id pyannote-segmentation-3.0
```
The `.oasr` container is GGUF-backed; every tensor is stored as raw f32 so the
pack round-trips bit-identically against the source weights.
## ⚖️ License
This pack **inherits the upstream model's license: MIT**
([source](https://huggingface.co/onnx-community/pyannote-segmentation-3.0)). OpenASR packaging retains the upstream copyright;
the only modification is format conversion.
## 🙏 Acknowledgements
This pack is a redistribution of **pyannote segmentation-3.0**, created by Hervé Bredin and the
**pyannote.audio** project, via the un-gated ONNX mirror
([onnx-community/pyannote-segmentation-3.0](https://huggingface.co/onnx-community/pyannote-segmentation-3.0)).
All credit for the architecture, training, and weights belongs to the upstream authors; the license
is inherited from and identical to the upstream model (MIT).
## 🔗 Links
- 🦀 **OpenASR** — <https://github.com/QuintinShaw/openasr>
- 🌐 **Website** — <https://openasr.org>
- 🤗 **Upstream model** — [onnx-community/pyannote-segmentation-3.0](https://huggingface.co/onnx-community/pyannote-segmentation-3.0) |