8th Annual Conference of the International Speech Communication Association

Antwerp, Belgium
August 27-31, 2007

Modelling Confusion Matrices to Improve Speech Recognition Accuracy, with an Application to Dysarthric Speech

Omar Caballero Morales, Stephen Cox

University of East Anglia, UK

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.

Full Paper

Bibliographic reference.  Morales, Omar Caballero / Cox, Stephen (2007): "Modelling confusion matrices to improve speech recognition accuracy, with an application to dysarthric speech", In INTERSPEECH-2007, 1565-1568.