Intelligibility detection of pathological speech using asymmetric sparse kernel partial least squares classifier

Dong-Yan Huang, Minghui Dong, Haizhou Li
2014 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
Pathological speech usually refers to the voice disorders resulting from atypicalities in voice and/or in the articulatory mechanisms due to disease, illness or other physical problem in the speech production system. It may increase unhealthy social behavior and voice abuse, and dramatically affect the patients' quality of life. Therefore, automatic intelligibility detection of pathological speech has an important role in the opportune treatment of pathological voices. This paper proposes to
more » ... asymmetric sparse kernel partial least squares classifier (ASKPLSC) for intelligibility detection of pathological speech. The proposed approach achieves an unweighted accuracy (UA) of 74.0%, which is 7.34% relative improvement of baseline system of an UA of 68.90% for the Pathology Sub-Challenge of INTERSPEECH 2012 Speaker Trait Challenge. Index Terms-Pathological speech, intelligibility of speech, kernel function, sparse kernel partial least squares regression, asymmetric sparse kernel partial least squares classifier
doi:10.1109/icassp.2014.6854301 dblp:conf/icassp/HuangDL14 fatcat:55omhytvmbc47ns5jkq5ox2ivq