a toolkit for reproducible evaluation, diagnostic, and error analysis of speaker diarization systems
An overview of pyannote.metrics is available as an InterSpeech 2017 paper: it is recommended to read it first, to quickly get an idea whether this tool is for you.
$ pip install pyannote.metricsThe documentation is available at http://pyannote.github.io/pyannote-metrics.
Sample notebooks are available here.
If you use pyannote.metrics in your research, please use the following citation:
@inproceedings{pyannote.metrics,
author = {Herv\'e Bredin},
title = {{pyannote.metrics: a toolkit for reproducible evaluation, diagnostic, and error analysis of speaker diarization systems}},
booktitle = {{Interspeech 2017, 18th Annual Conference of the International Speech Communication Association}},
year = {2017},
month = {August},
address = {Stockholm, Sweden},
url = {http://pyannote.github.io/pyannote-metrics},
}