Optimizing Bayesian Hmm Based X-Vector Clustering for the Second Dihard Speech Diarization Challenge
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F20%3APU136482" target="_blank" >RIV/00216305:26230/20:PU136482 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9053982" target="_blank" >https://ieeexplore.ieee.org/document/9053982</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICASSP40776.2020.9053982" target="_blank" >10.1109/ICASSP40776.2020.9053982</a>
Alternative languages
Result language
angličtina
Original language name
Optimizing Bayesian Hmm Based X-Vector Clustering for the Second Dihard Speech Diarization Challenge
Original language description
This paper presents an analysis of our diarization system winning the second DIHARD speech diarization challenge, track 1. This system is based on clustering x-vector speaker embeddings extracted every 0.25s from short segments of the input recording. In this paper, we focus on the two x-vector clustering methods employed, namely Agglomerative Hierarchical Clustering followed by a clustering based on Bayesian Hidden Markov Model (BHMM). Even though the system submitted to the challenge had further post-processing steps, we will show that using this BHMM solely is enough to achieve the best performance in the challenge. The analysis will show improvements achieved by optimizing individual processing steps, including a simple procedure to effectively perform "domain adaptation" by Probabilistic Linear Discriminant Analysis model interpolation. All experiments are performed in the DIHARD II evaluation framework.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/LQ1602" target="_blank" >LQ1602: IT4Innovations excellence in science</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISBN
978-1-5090-6631-5
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
6519-6523
Publisher name
IEEE Signal Processing Society
Place of publication
Barcelona
Event location
Barcelona
Event date
May 4, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000615970406156