Multi-Channel Speech Enhancement Based on Independent Vector Extraction

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F18%3A00006139" target="_blank" >RIV/46747885:24220/18:00006139 - isvavai.cz</a>
Result on the web
<a href="https://asap.ite.tul.cz/wp-content/uploads/sites/3/2018/09/iwaenc2018c.pdf" target="_blank" >https://asap.ite.tul.cz/wp-content/uploads/sites/3/2018/09/iwaenc2018c.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IWAENC.2018.8521330" target="_blank" >10.1109/IWAENC.2018.8521330</a>

Result language
angličtina
Original language name
Multi-Channel Speech Enhancement Based on Independent Vector Extraction
Original language description
In this paper, a gradient-based algorithm for Independent Vector Extraction is introduced and is first used for blind audio source extraction. We also propose novel modifications of the gradient learning rule in the algorithm based on preconditioning of input data and by using the AdaGrad update. Experiments with six-channel CHiME-4 recordings are conducted where the modified algorithms show significant improvement in terms of convergence speed.
Czech name
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Czech description
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Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
The 16th International Workshop on Acoustic Signal Enhancement (IWAENC 2018)
ISBN
978-1-5386-8151-0
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
525-529
Publisher name
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Place of publication
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Event location
Tokyo
Event date
Jan 1, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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