Publication result detail

Bayesian HMM based x-vector clustering for Speaker Diarization

DIEZ SÁNCHEZ, M.; BURGET, L.; WANG, S.; ROHDIN, J.; ČERNOCKÝ, J.

Original Title

Bayesian HMM based x-vector clustering for Speaker Diarization

English Title

Bayesian HMM based x-vector clustering for Speaker Diarization

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

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.

Keywords

Speaker Diarization, Variational Bayes, HMM,x-vector, DIHARD

Key words in English

Speaker Diarization, Variational Bayes, HMM,x-vector, DIHARD

Authors

DIEZ SÁNCHEZ, M.; BURGET, L.; WANG, S.; ROHDIN, J.; ČERNOCKÝ, J.

RIV year

2020

Released

15.09.2019

Publisher

International Speech Communication Association

Location

Graz

Book

Proceedings of Interspeech

ISBN

1990-9772

Periodical

Proceedings of Interspeech

Volume

2019

Number

9

State

French Republic

Pages from

346

Pages to

350

Pages count

5

URL

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"
}

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