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

Caballero-Morales, Omar and Cox, Stephen (2007) Modelling Confusion-Matrices to Improve Speech Recognition Accuracy, with an Application to Dysarthric Speech. In: 8th Annual Conference of the International Speech Communication Association (Interspeech), 2007-08-27 - 2007-08-31.

Full text not available from this repository. (Request a copy)

Abstract

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.

Item Type:	Conference or Workshop Item (Paper)
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Interactive Graphics and Audio Faculty of Science > Research Groups > Smart Emerging Technologies
Depositing User:	Vishal Gautam
Date Deposited:	04 Apr 2011 13:22
Last Modified:	22 Apr 2023 02:44
URI:	https://ueaeprints.uea.ac.uk/id/eprint/22339
DOI:

Actions (login required)

View Item