模型:
anilbs/segmentation
由Hervé Bredin和Antoine Laurent创建的模型。
Online demo 可在Hugging Face Space上获得。
如需商业咨询和科学咨询,请联系我。有关 technical questions 和 bug reports ,请查看 pyannote.audio 的Github存储库。
目前依赖于正在开发的pyannote.audio 2.0:请参见 installation instructions 。
from pyannote.audio.pipelines import VoiceActivityDetection pipeline = VoiceActivityDetection(segmentation="anilbs/segmentation") 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
from pyannote.audio.pipelines import OverlappedSpeechDetection pipeline = OverlappedSpeechDetection(segmentation="pyannote/segmentation") pipeline.instantiate(HYPER_PARAMETERS) osd = pipeline("audio.wav") # `osd` is a pyannote.core.Annotation instance containing overlapped speech regions
from pyannote.audio.pipelines import Resegmentation pipeline = Resegmentation(segmentation="pyannote/segmentation", 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
from pyannote.audio import Inference inference = Inference("pyannote/segmentation") segmentation = inference("audio.wav") # `segmentation` is a pyannote.core.SlidingWindowFeature # instance containing raw segmentation scores like the # one pictured above (output)
为了重现论文 "End-to-end speaker segmentation for overlap-aware resegmentation " 的结果,请使用以下超参数 pyannote/segmentation@Interspeech2021:
Voice activity detection | onset | offset | min_duration_on | min_duration_off |
---|---|---|---|---|
AMI Mix-Headset | 0.684 | 0.577 | 0.181 | 0.037 |
DIHARD3 | 0.767 | 0.377 | 0.136 | 0.067 |
VoxConverse | 0.767 | 0.713 | 0.182 | 0.501 |
Overlapped speech detection | onset | offset | min_duration_on | min_duration_off |
---|---|---|---|---|
AMI Mix-Headset | 0.448 | 0.362 | 0.116 | 0.187 |
DIHARD3 | 0.430 | 0.320 | 0.091 | 0.144 |
VoxConverse | 0.587 | 0.426 | 0.337 | 0.112 |
Resegmentation of VBx | onset | offset | min_duration_on | min_duration_off |
---|---|---|---|---|
AMI Mix-Headset | 0.542 | 0.527 | 0.044 | 0.705 |
DIHARD3 | 0.592 | 0.489 | 0.163 | 0.182 |
VoxConverse | 0.537 | 0.724 | 0.410 | 0.563 |
期望的输出(以及VBx基线)也提供在 /reproducible_research 子目录中。
@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}, }