Elderly Acoustic Model for Large Vocabulary Continuous Speech Recognition


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Please use this identifier to cite or link to this item: http://hdl.handle.net/10061/7953

Title:	Elderly Acoustic Model for Large Vocabulary Continuous Speech Recognition
Authors:	Akira Baba Shinichi Yoshizawa Miichi Yamada Akinobu Lee Kiyohiro Shikano
Issue Date:	Sep-2001
Start page:	1657
End page:	1660
Abstract:	In this paper, we evaluate elderly speaker acoustic models in LVCSR, which are trained by the 301 elderly speakers' database from the age of 60 to 90. Each speaker utters 200 sentences. The elderly speaker PTM (Phonetic Tied Mixture) acoustic model attains 88.9% word recognition rate, which is better than 86.0% word recognition rate by the usual adult (an average age of 28.6) PTM acoustic model. To achieve higher recognition rates, we use two types of speaker adaptation methods, which are a supervised MLLR and an unsupervised adaptation method based on the sufficient HMM statistics. In our experimental results, the elderly acoustic model is better as the adaptation baseline HMM model than the usual adult model for elderly speakers.
Description:	EUROSPEECH2001: the 7th European Conference on Speech Communication and Technology, September 3-7, 2001, Aalborg, Denmark.
URI:	http://hdl.handle.net/10061/7953
ISSN:	1018-4074
Rights:	Copyright 2001 ISCA
Text Version:	Publisher
Appears in Collections:	情報科学研究科 / Graduate School of Information Science

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