Bayesian HMM based x-vector clustering - VBx

Bayesovské shlukování x-vektorů založené na HMM - VBx

software

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Diez Sánchez Mireia, M.Sc., Ph.D. (DCGM)
Landini Federico Nicolás, Ph.D. (RG SPEECH)
Burget Lukáš, doc. Ing., Ph.D. (DCGM)

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

Diarization is the task of determining the number of speakers and "who speaks
when" in a recording. It is part of speech data mining. The proposed software
contains a full implementation of a Bayesian approach to do speaker diarization
using low-dimensional neural representation of speakers (x-vectors) in individual
segments. It follows the Brno University of Technology recipe for the Second
DIHARD Diarization Challenge Track 1, where BUT was the winner. It consists of
computing filter-bank features, computing x-vectors, performing Agglomerative
Hierarchical Clustering on x-vectors as a first step to produce an
initialization, applying Variational Bayes HMM over x-vectors to produce the
diarization output, and scoring the diarization output. The software is written
in Python and released as open-source under Apache License.

https://github.com/BUTSpeechFIT/VBx

• pdf diez_IEEE_ACM_2019_08910412.pdf 1 MB
• pdf diez_icassp2020_09053982.pdf 188 kB
• pdf landini_icassp2020_09054251.pdf 147 kB

IT4Innovations excellence in science, MŠMT, Národní program udržitelnosti II, LQ1602, start: 2016-01-01, end: 2020-12-31, completed
Moderní metody zpracování, analýzy a zobrazování multimediálních a 3D dat, BUT, Vnitřní projekty VUT, FIT-S-20-6460, start: 2020-03-01, end: 2023-02-28, 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, running
Robust SPEAKER DIariazation systems using Bayesian inferenCE and deep learning methods, EU, Horizon 2020, start: 2017-03-01, end: 2019-02-28, running

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

Department of Computer Graphics and Multimedia (DCGM)