Publication Details

Dealing with Unknowns in Continual Learning for End-to-end Automatic Speech Recognition

ŠŮSTEK Martin, SADHU Samik and HEŘMANSKÝ Hynek. Dealing with Unknowns in Continual Learning for End-to-end Automatic Speech Recognition. In: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH. Incheon: International Speech Communication Association, 2022, pp. 1046-1050. ISSN 1990-9772. Available from: https://www.isca-speech.org/archive/pdfs/interspeech_2022/sustek22_interspeech.pdf
Czech title
Vypořádání se s neznámými testovacími prostředími v kontextu kontinuálního učení a end-to-end automatického rozpoznávače řeči
Type
conference paper
Language
english
Authors
Šůstek Martin, Ing. (DCGM FIT BUT)
Sadhu Samik ()
Heřmanský Hynek, prof. Ing., Dr.Eng. (DCGM FIT BUT)
URL
Keywords

continual learning, multistream speech recognition, speech recognition

Abstract

Learning continually from data is a task executed effortlessly by humans but remains to be of significant challenge for machines. Moreover, when encountering unknown test scenarios machines fail to generalize. We propose a mathematically motivated dynamically expanding end-to-end model of independent sequence-to-sequence components trained on different data sets that avoid catastrophically forgetting knowledge acquired from previously seen data while seamlessly integrating knowledge from new data. During inference, the likelihoods of the unknown test scenario are computed using internal model activation distributions. The inference made by each independent component is weighted by the normalized likelihood values to obtain the final decision.

Published
2022
Pages
1046-1050
Journal
Proceedings of Interspeech - on-line, vol. 2022, no. 9, ISSN 1990-9772
Proceedings
Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Conference
Interspeech Conference, Incheon, KR
Publisher
International Speech Communication Association
Place
Incheon, KR
DOI
UT WoS
000900724501045
EID Scopus
BibTeX
@INPROCEEDINGS{FITPUB12945,
   author = "Martin \v{S}\r{u}stek and Samik Sadhu and Hynek He\v{r}mansk\'{y}",
   title = "Dealing with Unknowns in Continual Learning for End-to-end Automatic Speech Recognition",
   pages = "1046--1050",
   booktitle = "Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH",
   journal = "Proceedings of Interspeech - on-line",
   volume = 2022,
   number = 9,
   year = 2022,
   location = "Incheon, KR",
   publisher = "International Speech Communication Association",
   ISSN = "1990-9772",
   doi = "10.21437/Interspeech.2022-11139",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/12945"
}
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