Towards a noisy-channel model of dysarthria in speech recognition

Authors:
Frank Rudzicz
Affiliations:
University of Toronto, Toronto, Ontario, Canada
Venue:
SLPAT '10 Proceedings of the NAACL HLT 2010 Workshop on Speech and Language Processing for Assistive Technologies
Year:
2010

Citing 6
Cited 1

Numerical recipes in C (2nd ed.): the art of scientific computing

Numerical recipes in C (2nd ed.): the art of scientific computing
Improving the intelligibility of dysarthric speech

Speech Communication
Comparing speaker-dependent and speaker-adaptive acoustic models for recognizing dysarthric speech

Proceedings of the 9th international ACM SIGACCESS conference on Computers and accessibility
Statistical mapping between articulatory movements and acoustic spectrum using a Gaussian mixture model

Speech Communication
Review:

Neural Computation
Applying discretized articulatory knowledge to dysarthric speech

ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing

Dysarthric speech recognition error correction using weighted finite state transducers based on context---dependent pronunciation variation

ICCHP'12 Proceedings of the 13th international conference on Computers Helping People with Special Needs - Volume Part II

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Abstract

Modern automatic speech recognition is ineffective at understanding relatively unintelligible speech caused by neuro-motor disabilities collectively called dysarthria. Since dysarthria is primarily an articulatory phenomenon, we are collecting a database of vocal tract measurements during speech of individuals with cerebral palsy. In this paper, we demonstrate that articulatory knowledge can remove ambiguities in the acoustics of dysarthric speakers by reducing entropy relatively by 18.3%, on average. Furthermore, we demonstrate that dysarthric speech is more precisely portrayed as a noisy-channel distortion of an abstract representation of articulatory goals, rather than as a distortion of non-dysarthric speech. We discuss what implications these results have for our ongoing development of speech systems for dysarthric speakers.