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pyannote-audio
Neural building blocks for speaker diarization
Installation
$ conda create --name pyannote python=3.6 anaconda
$ source activate pyannote
$ conda install -c conda-forge yaafe
$ conda install cmake
$ pip install -U pip setuptools
$ pip install --process-dependency-links pyannote.audio
Citation
If you use pyannote.audio
in your research, please use the following citations.
- Speech activity and speaker change detection
@inproceedings{Yin2017, Author = {Ruiqing Yin and Herv\'e Bredin and Claude Barras}, Title = {{Speaker Change Detection in Broadcast TV using Bidirectional Long Short-Term Memory Networks}}, Booktitle = {{18th Annual Conference of the International Speech Communication Association, Interspeech 2017}}, Year = {2017}, Month = {August}, Address = {Stockholm, Sweden}, Url = {https://github.com/yinruiqing/change_detection} }
- Speaker embedding
@inproceedings{Bredin2017, author = {Herv\'{e} Bredin}, title = {{TristouNet: Triplet Loss for Speaker Turn Embedding}}, booktitle = {42nd IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2017}, year = {2017}, url = {http://arxiv.org/abs/1609.04301}, }
- Speaker diarization pipeline
@inproceedings{Yin2018, Author = {Ruiqing Yin and Herv\'e Bredin and Claude Barras}, Title = {{Neural Speech Turn Segmentation and Affinity Propagation for Speaker Diarization}}, Booktitle = {{19th Annual Conference of the International Speech Communication Association, Interspeech 2018}}, Year = {2018}, Month = {September}, Address = {Hyderabad, India}, }
Tutorials
- Feature extraction
- LSTM-based speech activity detection
- LSTM-based speaker change detection
- TristouNet neural speech turn embedding
- Speaker diarization pipeline
Documentation
The API is unfortunately not documented yet.