EUROSPEECH 2001 Scandinavia
7th European Conference on Speech Communication and Technology

Aalborg, Denmark
September 3-7, 2001


Elderly Acoustic Model for Large Vocabulary Continuous Speech Recognition

Akira Baba (1), Shinichi Yoshizawa (2), Miichi Yamada (3), Akinobu Lee (3), Kiyohiro Shikano (3)

(1) Matsushita Electric Works, Japan
(2) Matsushita Electric Industrial Co., Japan
(3) Nara Institute of Science and Technology, Japan

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.

Full Paper

Bibliographic reference.  Baba, Akira / Yoshizawa, Shinichi / Yamada, Miichi / Lee, Akinobu / Shikano, Kiyohiro (2001): "Elderly acoustic model for large vocabulary continuous speech recognition", In EUROSPEECH-2001, 1657-1660.