NDLI: Jacobian joint adaptation to noise, channel and vocal tract length

Content Provider	IEEE Xplore Digital Library
Author	Shimodaira, Hiroshi Sakai, Nobuyoshi Nakai, Mitsuru Sagayama, Shigeki
Copyright Year	2002
Description	Author affiliation: Japan Advanced Institute of Science and Technology, School Information Science, Tatsunokuchi, Ishikwaka 923-1292 Japan (Shimodaira, Hiroshi; Sakai, Nobuyoshi; Nakai, Mitsuru) \|\| The University of Tokyo, Graduate School of Information Science and Technology, Hongo, Bunkyo-ku, Tokyo 113-8654 Japan (Sagayama, Shigeki)
Abstract	A new Jacobian approach that linearly decomposes the composite of additive noise, multiplicative noise (channel transfer function) and speaker's vocal tract length, and adapts the acoustic model parameters simultaneously to these factors is proposed in this paper. Due to the fact that these factors non-linearly degrade the observed features for speech recognition, existing approaches fail to adapt the acoustic models adequately. Approximating the nonlinear operation by a linear model enables to employ the least square error estimation of the factors and adapt the acoustic model parameters with small amount of speech samples. Speech recognition experiments on ATR isolated word database demonstrate significant reduction of error rates, which supports the effectiveness of the proposed scheme.
File Size	1608173
File Format	PDF
ISBN	0780374029
ISSN	15206149
DOI	10.1109/ICASSP.2002.5743688
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-05-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Jacobian matrices Adaptation model Hidden Markov models Silicon Iron Speech Testing
Content Type	Text
Resource Type	Article

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