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

Omar Caballero-Morales, Stephen Cox

Research output: Contribution to conferencePaper

5 Citations (Scopus)


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.
Original languageEnglish
Publication statusPublished - 2007
Event8th Annual Conference of the International Speech Communication Association (Interspeech) - Antwerp, Belgium
Duration: 27 Aug 200731 Aug 2007


Conference8th Annual Conference of the International Speech Communication Association (Interspeech)

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