# 1. visit hf.co/pyannote/segmentation and accept user conditions# 2. visit hf.co/settings/tokens to create an access token# 3. instantiate pretrained modelfrom pyannote.audio import Model
model = Model.from_pretrained("pyannote/segmentation",
use_auth_token="ACCESS_TOKEN_GOES_HERE")
Voice activity detection
from pyannote.audio.pipelines import VoiceActivityDetection
pipeline = VoiceActivityDetection(segmentation=model)
HYPER_PARAMETERS = {
# onset/offset activation thresholds"onset": 0.5, "offset": 0.5,
# remove speech regions shorter than that many seconds."min_duration_on": 0.0,
# fill non-speech regions shorter than that many seconds."min_duration_off": 0.0
}
pipeline.instantiate(HYPER_PARAMETERS)
vad = pipeline("audio.wav")
# `vad` is a pyannote.core.Annotation instance containing speech regions
Overlapped speech detection
from pyannote.audio.pipelines import OverlappedSpeechDetection
pipeline = OverlappedSpeechDetection(segmentation=model)
pipeline.instantiate(HYPER_PARAMETERS)
osd = pipeline("audio.wav")
# `osd` is a pyannote.core.Annotation instance containing overlapped speech regions
Resegmentation
from pyannote.audio.pipelines import Resegmentation
pipeline = Resegmentation(segmentation=model,
diarization="baseline")
pipeline.instantiate(HYPER_PARAMETERS)
resegmented_baseline = pipeline({"audio": "audio.wav", "baseline": baseline})
# where `baseline` should be provided as a pyannote.core.Annotation instance
Raw scores
from pyannote.audio import Inference
inference = Inference(model)
segmentation = inference("audio.wav")
# `segmentation` is a pyannote.core.SlidingWindowFeature# instance containing raw segmentation scores like the # one pictured above (output)
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},
}
segmentation huggingface.co is an AI model on huggingface.co that provides segmentation's model effect (), which can be used instantly with this pyannote segmentation model. huggingface.co supports a free trial of the segmentation model, and also provides paid use of the segmentation. Support call segmentation model through api, including Node.js, Python, http.
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