NDLI: Instantaneous model adaptation method for reverberant speech recognition

Content Provider	IET Digital Library
Author	Ban, Sung Min Kim, Hyung Soon
Abstract	An acoustic model adaptation algorithm is proposed for reverberant speech recognition. Inspired by the eigenvoice adaptation framework, multiple acoustic models reflecting various reverberant environments are combined for instantaneous adaptation. Using artificially generated reverberant speech, multiple acoustic models are trained according to multiple reverberation times. The mean vectors of the optimal acoustic model are obtained as a weighted sum of those of multiple acoustic models by using a maximum-likelihood criterion. For effective model combination, reverberant speech is preprocessed. Experiments on English continuous speech recognition tasks in a simulated reverberant environment show that the proposed method performs better than the conventional adaptation techniques.
Starting Page	528
Ending Page	530
Page Count	3
ISSN	00135194
Volume Number	51
e-ISSN	1350911X
Issue Number	Issue 6, Mar (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/51/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2014.4152
Journal	Electronics Letters
Publisher Date	2015-03-04
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Acoustic Model Adaptation Algorithm Acoustic Signal Processing Algebra Eigen Values And Eigen Function Eigenvoice Adaptation Framework English Continuous Speech Recognition Task Instantaneous Model Adaptation Method Maximum Likelihood Estimation Maximum-likelihood Criterion Mean Vector Model Combination Multiple Acoustic Model Multiple Reverberation Times Natural Language Processing Reverberant Environments Reverberant Speech Recognition Speech Processing Technique Speech Recognition Speech Recognition And Synthesis Statistics Vector
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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