Result Details

Bayesian HMM based x-vector clustering for Speaker Diarization

DIEZ SÁNCHEZ, M.; BURGET, L.; WANG, S.; ROHDIN, J.; ČERNOCKÝ, J. Bayesian HMM based x-vector clustering for Speaker Diarization. In Proceedings of Interspeech. Proceedings of Interspeech. Graz: International Speech Communication Association, 2019. no. 9, p. 346-350. ISSN: 1990-9772.

Type

conference paper

Language

English

Authors

Diez Sánchez Mireia, M.Sc., Ph.D., DCGM (FIT)
Burget Lukáš, doc. Ing., Ph.D., DCGM (FIT)
Wang Shuai, DCGM (FIT)
Rohdin Johan Andréas, M.Sc., Ph.D., FIT (FIT), DCGM (FIT)
Černocký Jan, prof. Dr. Ing., DCGM (FIT)

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

URL

Published

2019

Pages

346–350

Journal

Proceedings of Interspeech, vol. 2019, no. 9, ISSN 1990-9772

Proceedings

Proceedings of Interspeech

Conference

Interspeech Conference

Publisher

International Speech Communication Association

Place

Graz

DOI

10.21437/Interspeech.2019-2813

UT WoS

000831796400070

EID Scopus

2-s2.0-85079021117

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"
}

Files

pdf diez_is2019_192813.pdf 163 kB

Projects

Information mining in speech acquired by distant microphones, MV, Bezpečnostní výzkum České republiky 2015-2020, VI20152020025, start: 2015-10-01, end: 2020-09-30, completed
IT4Innovations excellence in science, MŠMT, Národní program udržitelnosti II, LQ1602, start: 2016-01-01, end: 2020-12-31, completed
Neural Representations in multi-modal and multi-lingual modeling, GACR, Grantové projekty exelence v základním výzkumu EXPRO - 2019, GX19-26934X, start: 2019-01-01, end: 2023-12-31, completed
Robust SPEAKER DIariazation systems using Bayesian inferenCE and deep learning methods, EU, Horizon 2020, start: 2017-03-01, end: 2019-02-28, completed
Sequence summarizing neural networks for speaker recognition, EU, Horizon 2020, 5SA15094, start: 2016-07-01, end: 2019-06-30, completed
Zpracování, zobrazování a analýza multimediálních a 3D dat, BUT, Vnitřní projekty VUT, FIT-S-17-3984, start: 2017-03-01, end: 2020-02-29, completed

Research groups

Speech Data Mining Research Group BUT Speech@FIT (RG SPEECH)

Departments

Department of Computer Graphics and Multimedia (DCGM)