metadata

tags:
  - pyannote
  - pyannote-audio
  - pyannote-audio-pipeline
  - audio
  - voice
  - speech
  - speaker
  - speaker-segmentation
  - speaker-diarization
  - speaker-change-detection
  - voice-activity-detection
  - overlapped-speech-detection
  - automatic-speech-recognition
datasets:
  - ami
  - dihard
  - voxconverse
license: mit
extra_gated_prompt: >-
  The collected information will help acquire a better knowledge of
  pyannote.audio userbase and help its maintainers apply for grants to improve
  it further. If you are an academic researcher, please cite the relevant papers
  in your own publications using the model. If you work for a company, please
  consider contributing back to pyannote.audio development (e.g. through
  unrestricted gifts). We also provide scientific consulting services around
  speaker diarization and machine listening.
extra_gated_fields:
  Company/university: text
  Website: text
  I plan to use this model for (task, type of audio data, etc): text

Using this open-source model in production?
Consider switching to pyannoteAI for better and faster options.

🎹 Speaker segmentation

Relies on pyannote.audio 2.1: see installation instructions.

# 1. visit hf.co/pyannote/segmentation and accept user conditions
# 2. visit hf.co/settings/tokens to create an access token
# 3. instantiate pretrained speaker segmentation pipeline
from pyannote.audio import Pipeline
pipeline = Pipeline.from_pretrained("pyannote/speaker-segmentation")
output = pipeline("audio.wav")

for turn, _, speaker in output.itertracks(yield_label=True):
    # speaker speaks between turn.start and turn.end
    ...

⚠️ This pipeline does not address speaker diarization.

Support

For commercial enquiries and scientific consulting, please contact me.
For technical questions and bug reports, please check pyannote.audio Github repository.

Citation

@inproceedings{Bredin2021,
  Title = {{End-to-end speaker segmentation for overlap-aware resegmentation}},
  Author = {{Bredin}, Herv{\'e} and {Laurent}, Antoine},
  Booktitle = {Proc. Interspeech 2021},
  Address = {Brno, Czech Republic},
  Month = {August},
  Year = {2021},

@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},
}