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DIEZ SÁNCHEZ, M.; BURGET, L.; WANG, S.; ROHDIN, J.; ČERNOCKÝ, J.
Original Title
Bayesian HMM based x-vector clustering for Speaker Diarization
English Title
Type
Paper in proceedings (conference paper)
Original Abstract
This paper presents a simplified version of the previously proposeddiarization algorithm based on Bayesian Hidden MarkovModels, which uses Variational Bayesian inference for very fastand robust clustering of x-vector (neural network based speakerembeddings). The presented results show that this clusteringalgorithm provides significant improvements in diarization performanceas compared to the previously used AgglomerativeHierarchical Clustering. The output of this system can be furtheremployed as an initialization for a second stage VB diarizationsystem, using frame-wise MFCC features as input, to obtainoptimal results.
English abstract
Keywords
Speaker Diarization, Variational Bayes, HMM,x-vector, DIHARD
Key words in English
Authors
RIV year
2020
Released
15.09.2019
Publisher
International Speech Communication Association
Location
Graz
Book
Proceedings of Interspeech
ISBN
1990-9772
Periodical
Volume
2019
Number
9
State
French Republic
Pages from
346
Pages to
350
Pages count
5
URL
https://www.isca-speech.org/archive/Interspeech_2019/pdfs/2813.pdf
BibTex
@inproceedings{BUT159992, author="Mireia {Diez Sánchez} and Lukáš {Burget} and Shuai {Wang} and Johan Andréas {Rohdin} and Jan {Černocký}", title="Bayesian HMM based x-vector clustering for Speaker Diarization", booktitle="Proceedings of Interspeech", year="2019", journal="Proceedings of Interspeech", volume="2019", number="9", pages="346--350", publisher="International Speech Communication Association", address="Graz", doi="10.21437/Interspeech.2019-2813", issn="1990-9772", url="https://www.isca-speech.org/archive/Interspeech_2019/pdfs/2813.pdf" }
Documents
diez_is2019_192813