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  ---
 
 
 
 
 
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  license: mit
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  language:
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  - en
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  ```
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  for speech_turn, track, speaker in diarization.itertracks(yield_label=True):
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  print(f"{speech_turn.start:4.1f} {speech_turn.end:4.1f} {speaker}")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
 
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  ---
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+ tags:
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+ - pyannote
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+ - pyannote-audio
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+ - pyannote-audio-pipeline
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+ - speaker-diarization
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  license: mit
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  language:
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  - en
 
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  ```
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  for speech_turn, track, speaker in diarization.itertracks(yield_label=True):
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  print(f"{speech_turn.start:4.1f} {speech_turn.end:4.1f} {speaker}")
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+ ```
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+
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+ ## Citations
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+
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+ ```bibtex
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+ @inproceedings{Plaquet23,
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+ author={Alexis Plaquet and Hervé Bredin},
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+ title={{Powerset multi-class cross entropy loss for neural speaker diarization}},
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+ year=2023,
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+ booktitle={Proc. INTERSPEECH 2023},
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+ }
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+ ```
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+
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+ ```bibtex
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+ @inproceedings{Bredin23,
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+ author={Hervé Bredin},
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+ title={{pyannote.audio 2.1 speaker diarization pipeline: principle, benchmark, and recipe}},
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+ year=2023,
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+ booktitle={Proc. INTERSPEECH 2023},
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+ }
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  ```