readme: ---
  tags:
  - pyannote
  - audio
  - voice-activity-detection
  datasets:
  - dihard
  license: mit
  inference: false
  ---
  
  ## Example pyannote-audio Voice Activity Detection model 
  
  ### `pyannote.audio.models.segmentation.PyanNet`
  
  ♻️ Imported from https://github.com/pyannote/pyannote-audio-hub
  
  This model was trained by @hbredin.
  
  
  ### Demo: How to use in pyannote-audio
  
  ```python
  from pyannote.audio.core.inference import Inference
  
  model = Inference('julien-c/voice-activity-detection', device='cuda')
  model({
  	"audio": "TheBigBangTheory.wav"
  })
  ```
  
  ### Citing pyannote-audio
  
  ```BibTex
  @inproceedings{Bredin2020,
    Title = {{pyannote.audio: neural building blocks for speaker diarization}},
    Author = {{Bredin}, Herv{\'e} and {Yin}, Ruiqing and {Coria}, Juan Manuel and {Gelly}, Gregory and {Korshunov}, Pavel and {Lavechin}, Marvin and {Fustes}, Diego and {Titeux}, Hadrien and {Bouaziz}, Wassim and {Gill}, Marie-Philippe},
    Booktitle = {ICASSP 2020, IEEE International Conference on Acoustics, Speech, and Signal Processing},
    Address = {Barcelona, Spain},
    Month = {May},
    Year = {2020},
  }
  ```
  
  or
  
  ```bibtex
  @inproceedings{Lavechin2020,
      author = {Marvin Lavechin and Marie-Philippe Gill and Ruben Bousbib and Herv\'{e} Bredin and Leibny Paola Garcia-Perera},
      title = {{End-to-end Domain-Adversarial Voice Activity Detection}},
      year = {2020},
      url = {https://arxiv.org/abs/1910.10655},
  }
  ```
  
  