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Optimizing Vocabulary Modeling for Dysarthric Speech Recognition

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Authors
Na, Minsoo; Chung, Minhwa
Issue Date
2016-07-15
Publisher
SPRINGER INTERNATIONAL PUBLISHING SWITZERLAND
Citation
Proceeding of 15th International Conference on Computers Helping People with Special Needs, pp. 507-510
Keywords
DysarthriaVocabulary modelingSpeech recognition
Abstract
Imperfection in articulation of dysarthric speech results in the deterioration on the performance of speech recognition. In this paper, the effect of the articulating class of phonemes in the dysarthric speech recognition results is analyzed using generalized linear mixed models (GLMMs). The model with the features categorized according to the manner of articulation and the place of tongue is selected as the best one by the analysis. Recognition accuracy score for each word is predicted based on its pronunciation and the GLMM. The vocabulary optimized by selecting words with the maximum score shows a 16.4 % relative error reduction in dysarthric speech recognition.
ISSN
0302-9743
Language
English
URI
http://hdl.handle.net/10371/117484
DOI
https://doi.org/10.1007/978-3-319-41267-2_71
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College of Humanities (인문대학)Linguistics (언어학과)Journal Papers (저널논문_언어학과)
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