Integration of metamodel and acoustic model for speech recognition
Hironori Matsumasa, Tetsuya Takiguchi, Yasuo Ariki, Ichao Li, Toshitaka Nakabayashi · 2008
We investigated the speech recognition of a person with artic-ulation disorders resulting from athetoid cerebral palsy. The articulation of the first speech tends to become unstable due to strain on speech-related muscles, and that causes degradation of speech recognition. Therefore, we proposed a robust feature extraction method based on PCA (Principal Component Analy-sis) instead of MFCC [1]. In this paper, we discuss our effort to integrate a Metamodel [2] and Acoustic model approach. Meta-model has a technique for incorporating a model of a speaker’s confusion matrix into the ASR process in such a way as to increase recognition accuracy. Its effectiveness has been con-firmed by word recognition experiments. Index Terms: articulation disorders, PCA, feature extraction, model integration, dysarthric speech