Modelling confusion matrices to improve speech recognition accuracy, with an application to dysarthric speech
نویسندگان
چکیده
Dysarthria is a motor speech disorder characterized by weakness, paralysis, or poor coordination of the muscles responsible for speech. Although automatic speech recognition (ASR) systems have been developed for disordered speech, factors such as low intelligibility and limited vocabulary decrease speech recognition accuracy. In this paper, we introduce a technique that can increase recognition accuracy in speakers with low intelligibility by incorporating information from an estimate of the speaker’s phoneme confusion matrix. The technique performs much better than standard speaker adaptation when the number of sentences available from a speaker for confusion matrix estimation or adaptation is low, and has similar performance for larger numbers of sentences.
منابع مشابه
On the estimation and the use of confusion-matrices for improving ASR accuracy
In previous work, we described how learning the pattern of recognition errors made by an individual using a certain ASR system leads to increased recognition accuracy compared with a standard MLLR adaptation approach. This was the case for low-intelligibility speakers with dysarthric speech, but no improvement was observed for normal speakers. In this paper, we describe an alternative method fo...
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Dysarthria is a motor speech disorder characterized by weakness, paralysis, or poor coordination of the muscles responsible for speech. Although automatic speech recognition (ASR) systems have been developed for disordered speech, factors such as low intelligibility and limited phonemic repertoire decrease speech recognition accuracy, making conventional speaker adaptation algorithms perform po...
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