pyannote audio: neural building blocks for speaker diarization
Channel: Hervé Bredin
Date: 2020-04-16

We introduce pyannote.audio, an open-source toolkit written in Python for speaker diarization. Based on PyTorch machine learning framework, it provides a set of trainable end-to-end neural building blocks that can be combined and jointly optimized to build speaker diarization pipelines. pyannote.audio also comes with pre-trained models covering a wide range of domains for voice activity detection, speaker change detection, overlapped speech detection, and speaker embedding.

Code: https://github.com/pyannote/pyannote-audio 

Paper: https://arxiv.org/abs/1911.01255