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RISS 인기검색어

Rapid adaptation using linear spectral transformation for embedded speech recognisers

한글로보기

https://www.riss.kr/link?id=A107754859

저자

Cho, Y. ; Yook, D.
발행기관
IET
학술지명
Electronics letters
권호사항

Vol.44 No.17 [2008]
발행연도
2008
작성언어
-
등재정보
SCOPUS,SCIE
자료형태
학술저널
수록면

1040-1042(3쪽)
제공처
ScienceON

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다국어 초록 (Multilingual Abstract)

Embedded speech recognisers are typically used in unknown mobile environments where the acoustic conditions frequently change. Since a large amount of adaptation data is not usually available for such environments, the adaptation methods for the acoustic models of these recognisers must improve the recognition performance with only a small amount of adaptation data. In this Letter, we show that maximum likelihood linear spectral transformation provides the advantage of rapid adaptation using a very limited amount of adaptation data for the embedded acoustic models.

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Embedded speech recognisers are typically used in unknown mobile environments where the acoustic conditions frequently change. Since a large amount of adaptation data is not usually available for such environments, the adaptation methods for ...

Embedded speech recognisers are typically used in unknown mobile environments where the acoustic conditions frequently change. Since a large amount of adaptation data is not usually available for such environments, the adaptation methods for the acoustic models of these recognisers must improve the recognition performance with only a small amount of adaptation data. In this Letter, we show that maximum likelihood linear spectral transformation provides the advantage of rapid adaptation using a very limited amount of adaptation data for the embedded acoustic models.