Automatic speech recognition and training for severely dysarthric users of assistive technology: The STARDUST project

被引:32
|
作者
Parker, M
Cunningham, S
Enderby, P
Hawley, M
Green, P
机构
[1] Univ Sheffield, Dept Human Commun Sci, Sheffield S10 2TN, S Yorkshire, England
[2] Sheffield Speech & Language Therapy Agcy, Sheffield, S Yorkshire, England
[3] Univ Sheffield, Inst Gen Practice, Sheffield S10 2TN, S Yorkshire, England
[4] Barnsley Dist Gen Hosp NHS Trust, Dept Med Phys & Clin Engn, Barnsley, England
[5] Univ Sheffield, Dept Comp Sci, Sheffield S10 2TN, S Yorkshire, England
关键词
dysarthria; automatic speech recognition; articulation; assistive technology; speech training; treatment;
D O I
10.1080/02699200400026884
中图分类号
R36 [病理学]; R76 [耳鼻咽喉科学];
学科分类号
100104 ; 100213 ;
摘要
The STARDUST project developed robust computer speech recognizers for use by eight people with severe dysarthria and concomitant physical disability to access assistive technologies. Independent computer speech recognizers trained with normal speech are of limited functional use by those with severe dysarthria due to limited and inconsistent proximity to "normal'' articulatory patterns. Severe dysarthric output may also be characterized by a small mass of distinguishable phonetic tokens making the acoustic differentiation of target words difficult. Speaker dependent computer speech recognition using Hidden Markov Models was achieved by the identification of robust phonetic elements within the individual speaker output patterns. A new system of speech training using computer generated visual and auditory feedback reduced the inconsistent production of key phonetic tokens over time.
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页码:149 / 156
页数:8
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