
# Speaker diarization

Relies on pyannote.audio 2.0 currently in development: see [installation instructions](https://github.com/pyannote/pyannote-audio/tree/develop#installation).

```python
from pyannote.audio import Pipeline
pipeline = Pipeline.from_pretrained("AMITKESARI2000/pyannote_SD1")
output = pipeline("audio.wav")
for turn, _, speaker in output.itertracks(yield_label=True):
    # speaker speaks between turn.start and turn.end
    ...
```

## Benchmark 

| Dataset                                                                                             | [Diarization error rate](http://pyannote.github.io/pyannote-metrics/reference.html#diarization) |
| --------------------------------------------------------------------------------------------------- | ------ |
| [AMI `only_words` evaluation set](https://github.com/BUTSpeechFIT/AMI-diarization-setup)            | 21.4% |

{"license": "mit", "tags": ["pyannote", "speaker-diarization"], "datasets": ["ami", "voxconverse"]}
pyannote speaker-diarization dataset:ami dataset:voxconverse license:mit region:us
TAGS
#pyannote #speaker-diarization #dataset-ami #dataset-voxconverse #license-mit #region-us 

Speaker diarization
===================


Relies on URL 2.0 currently in development: see installation instructions.


Benchmark
---------




TAGS
#pyannote #speaker-diarization #dataset-ami #dataset-voxconverse #license-mit #region-us 

passage: TAGS
#pyannote #speaker-diarization #dataset-ami #dataset-voxconverse #license-mit #region-us 
