Two-Step Acoustic Model Adaptation For Dysarthric Speech Recognition
Ryoichi Takashima, Tetsuya Takiguchi, Yasuo Ariki
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This paper introduces a model adaptation approach for a speaker-dependent dysarthric speech recognition system. The dysarthria we focus on in this paper is caused by athetoid cerebral palsy, which causes involuntary muscle movements in those with the disease. For this reason, the dysarthric people's speech is often unstable and difficult for conventional automatic speech recognition (ASR) systems to recognize. A model-adaptation approach, which adapts an ASR model to dysarthric speech, is one possible solution. However, because the difference in speaking styles between dysarthric and non-dysarthric people is so significant, the conventional adaptation method is not able to sufficiently adapt the model to the dysarthric speech. In our proposed two-step model-adaptation approach, an ASR model is first adapted to the general speaking style of multiple dysarthric speakers, and then the adapted model is further adapted for the target speaker. From our experiments on an ASR task, our two-step adaptation approach showed better performance than a conventional one-step adaptation approach.