---
license: mit
datasets:
- ami
language:
- en
library_name: pyannote-audio
pipeline_tag: voice-activity-detection
tags:
- chime7_task1
---

## Pyannote Segmentation model fine-tuned on CHiME-7 DASR data

This repo contains the [Pyannote Segmentation](https://huggingface.co/pyannote/segmentation/tree/main) model fine-tuned on data from CHiME-7 DASR Challenge. 
Only CHiME-6 (train set) data was used for training while Mixer 6 (dev set) was used for validation in order to avoid overfitting CHiME-6 scenario 
(Mixer 6 is arguably the most different scenario within the three in CHiME-7 DASR so I used it in validation here as the ultimate score is a macro-average across all scenarios). 

It is used to perform diarization in the CHiME-7 DASR diarization baseline. <br> 
**For more information see the [CHiME-7 DASR baseline recipe in ESPNEt2](https://github.com/espnet/espnet/egs2/chime7_task1/diar_asr1).**

## Usage

Relies on pyannote.audio 2.1.1: see [installation instructions](https://github.com/pyannote/pyannote-audio).

```python
from pyannote.audio import Model
model = Model.from_pretrained("popcornell/pyannote-segmentation-chime6-mixer6")
```