Voice-activity and overlapped speech detection using x-vectors
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F20%3A00008350" target="_blank" >RIV/46747885:24220/20:00008350 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-030-58323-1_40" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-58323-1_40</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-58323-1_40" target="_blank" >10.1007/978-3-030-58323-1_40</a>
Alternative languages
Result language
angličtina
Original language name
Voice-activity and overlapped speech detection using x-vectors
Original language description
The x-vectors are features extracted from speech signals using pretrained deep neural networks, such that they discriminate well among different speakers. Their main application lies in speaker identification and verification. This manuscript studies, which other properties are encoded in x-vectors. The focus lies on distinguishing between speech signals/noise and utterances of a single speaker versus overlapped-speech. We attempt to show that the x-vector network is capable to extract multi-purpose features, which can be used by several simple back-end classifiers. This means a common feature extracting front-end for the tasks of voice-activity/overlapped speech detection and speaker identification. Compared to the alternative strategy, that is training of independent classifiers including feature extracting layers for each of the tasks, the common front-end saves computational time during both training and test phase.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
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/TH03010018" target="_blank" >TH03010018: DeepSpot - Multilingual technology for spotting and instant alerting</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
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
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) - 23rd International Conference on Text, Speech, and Dialogue, TSD 2020
ISBN
978-303058322-4
ISSN
03029743
e-ISSN
—
Number of pages
11
Pages from-to
366-376
Publisher name
Springer Nature Switzerland
Place of publication
Switzerland
Event location
(on-line) Brno, Czech Republic
Event date
Jan 1, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000611543200040