Preprint
pyannote.audio: neural building blocks for speaker diarization
Hervé Bredin et al., arXiv (submitted to ICASSP 2020), 2019
Read the originalRead on October 17, 2026
- What it is
- The paper introduces pyannote.audio, an open-source Python toolkit for speaker diarization built on PyTorch. It provides trainable neural components for voice activity detection, speaker change detection, overlapped speech detection and speaker embedding, with pre-trained models.
- How much weight it carries
- A preprint from the toolkit's authors, reviewed through its arXiv abstract only. It describes the design of an open-source tool, not how accurate any pipeline is on a given recording, so accuracy figures need the later model cards and papers.
Facts taken from this source
- The pyannote.audio paper describes an open-source toolkit written in Python for speaker diarization, with pre-trained models for voice activity detection, speaker change detection, overlapped speech detection and speaker embedding.
“an open-source toolkit written in Python for speaker diarization” (Abstract)