Publication Details

Deep Auto-encoder Based Multi-task Learning Using Probabilistic Transcriptions

DAS Amit, HASEGAWA-JOHNSON Mark and VESELÝ Karel. Deep Auto-encoder Based Multi-task Learning Using Probabilistic Transcriptions. In: Proceedings of Interspeech 2017. Stockholm: International Speech Communication Association, 2017, pp. 2073-2077. ISSN 1990-9772. Available from: http://www.isca-speech.org/archive/Interspeech_2017/pdfs/0582.PDF
Czech title
Multi-task trénování s pravděpodobnostními přepisy založené na hlubokém autoenkodéru
Type
conference paper
Language
english
Authors
Das Amit (UILLINOIS)
Hasegawa-Johnson Mark (UILLINOIS)
Veselý Karel, Ing., Ph.D. (DCGM FIT BUT)
URL
Keywords

cross-lingual speech recognition, probabilistic transcription, deep neural networks, multi-task learning

Abstract

This article is about deep auto-encoder based Multi-task Learning using probabilistic transcriptions.

Published
2017
Pages
2073-2077
Journal
Proceedings of Interspeech - on-line, vol. 2017, no. 8, ISSN 1990-9772
Proceedings
Proceedings of Interspeech 2017
Conference
Interspeech Conference, Stockholm, SE
Publisher
International Speech Communication Association
Place
Stockholm, SE
DOI
10.21437/Interspeech.2017-582
UT WoS
000457505000434
EID Scopus
2-s2.0-85039159851
BibTeX 
@INPROCEEDINGS{FITPUB11585,
   author = "Amit Das and Mark Hasegawa-Johnson and Karel Vesel\'{y}",
   title = "Deep Auto-encoder Based Multi-task Learning Using Probabilistic Transcriptions",
   pages = "2073--2077",
   booktitle = "Proceedings of Interspeech 2017",
   journal = "Proceedings of Interspeech - on-line",
   volume = 2017,
   number = 08,
   year = 2017,
   location = "Stockholm, SE",
   publisher = "International Speech Communication Association",
   ISSN = "1990-9772",
   doi = "10.21437/Interspeech.2017-582",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/11585"
}
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