Automatic speaker independent dysarthric speech intelligibility assessment system

被引:6
|
作者
Tripathi, Ayush [1 ]
Bhosale, Swapnil [1 ]
Kopparapu, Sunil Kumar [1 ]
机构
[1] Tata Consultancy Serv Ltd, TCS Res, Chennai, Tamil Nadu, India
来源
关键词
Dysarthria; Speech intelligibility; Assessment; Pathological; DeepSpeech; VOWEL SPACE; CLASSIFICATION; HYPERNASALITY; ROBUST;
D O I
10.1016/j.csl.2021.101213
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Dysarthria is a condition which hampers the ability of an individual to control the muscles that play a major role in speech delivery. The loss of fine control over muscles that assist the movement of lips, vocal chords, tongue and diaphragm results in abnormal speech delivery. One can assess the severity level of dysarthria by analyzing the intelligibility of speech spoken by an individual. Continuous intelligibility assessment helps speech language pathologists not only study the impact of medication but also allows them to plan personalized therapy. It helps the clinicians immensely if the intelligibility assessment system is reliable, automatic, simple for (a) patients to undergo and (b) clinicians to interpret. Lack of availability of dysarthric data has resulted in development of speaker dependentautomatic intelligibility assessment systems which requires patients to speak a large number of utterances. In this paper, we propose (a) a cost minimization procedure to select an optimal (small) number of utterances that need to be spoken by the dysarthric patient, (b) four different speaker independent intelligibility assessment systems which require the patient to speak a small number of words, and (c) the assessment score is close to the perceptual score that the Speech Language Pathologist (SLP) can relate to. The need for small number of utterances to be spoken by the patient and the score being relatable to the SLP benefits both the dysarthric patient and the clinician from usability perspective. ? 2021 Elsevier Ltd. All rights reserved.
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页数:17
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