Abstract
Dysarthria is a speech motor disorder usually resulting in a substantive decrease in speech intelligibility by the general population. In this study, we have significantly improved the intelligibility of dysarthric vowels of one speaker from 48% to 54%, as evaluated by a vowel identification task using 64 CVC stimuli judged by 24 listeners. Improvement was obtained by transforming the vowels of a speaker with dysarthria to more closely match the vowel space of a non-dysarthric (target) speaker. The optimal mapping feature set, from a list of 21 candidate feature sets, proved to be one utilizing vowel duration and F1-F3 stable points, which were calculated using shape-constrained isotonic regression. The choice of speaker-specific or speaker-independent vowel formant targets appeared to be insignificant. Comparisons with "oracle" conditions were performed in order to evaluate the analysis/re-synthesis system independently of the transformation function.
Original language | English (US) |
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Pages (from-to) | 743-759 |
Number of pages | 17 |
Journal | Speech Communication |
Volume | 49 |
Issue number | 9 |
DOIs | |
State | Published - Sep 2007 |
Keywords
- Dysarthria
- Intelligibility
- Speech modification
- Speech processing
- Speech transformation
ASJC Scopus subject areas
- Software
- Modeling and Simulation
- Communication
- Language and Linguistics
- Linguistics and Language
- Computer Vision and Pattern Recognition
- Computer Science Applications