Advanced Search
Japanese | English

naistar (NAIST Academic Repository) >
学術リポジトリ naistar / NAIST Academic Repository naistar >
国際会議発表論文 / Proceedings >
情報科学研究科 / Graduate School of Information Science >

Please use this identifier to cite or link to this item:

Title: Model Adaptation based on HMM decomposition for Reverberant Speech Recognition
Authors: Tetsuya Takiguchi
Satoshi Nakamura
Qiang Huo
Kiyohiro Shikano
Issue Date: Apr-1997
Publisher: IEEE
Start page: 827
End page: 830
Abstract: The performance of a speech recognizer is degraded drastically in reverberant environments. The authors propose a novel algorithm which can model an observation signal by composition of HMMs of clean speech, noise and an acoustic transfer function. However, estimating HMM parameters of the acoustic transfer function is still a serious problem. In their previous paper, they measured real impulse responses of training positions in an experiment room. It is inconvenient and unrealistic to measure impulse responses for every possible new experiment room. The paper presents a new method for estimating HMM parameters of the acoustic transfer function from some adaptation data by using an HMM decomposition algorithm which is an inverse process of the HMM composition. Its effectiveness is confirmed by a series of speaker dependent and independent word recognition experiments on simulated distant-talking speech data
Description: ICASSP1997: IEEE International Conference on Acoustics, Speech, and Signal Processing, April 21-24, 1997.
ISBN: 0818679190
ISSN: 1520-6149
Rights: Copyright 1997 IEEE
Text Version: Publisher
Publisher DOI: 10.1109/ICASSP.1997.596060
Appears in Collections:情報科学研究科 / Graduate School of Information Science

Files in This Item:

File SizeFormat
ICASSP_1997_827.pdf471.01 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.


Copyright (c) 2007-2012 Nara Institute of Science and Technology All Rights Reserved.
DSpace Software Copyright © 2002-2010  Duraspace - Feedback