tailieunhanh - báo cáo hóa học:" Research Article Linear Classifier with Reject Option for the Detection of Vocal Fold Paralysis and Vocal Fold Edema"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Linear Classifier with Reject Option for the Detection of Vocal Fold Paralysis and Vocal Fold Edema | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2009 Article ID 203790 13 pages doi 2009 203790 Research Article Linear Classifier with Reject Option for the Detection of Vocal Fold Paralysis and Vocal Fold Edema Constantine Kotropoulos EURASIP Member 1 2 and Gonzalo R. Arce2 department of Informatics Aristotle University of Thessaloniki Thessaloniki 54124 Box451 Greece department of Electrical and Computer Engineering University of Delaware 140 Evans Hall Newark DE 19716 USA Correspondence should be addressed to Constantine Kotropoulos costas@ Received 1 November 2008 Revised 19 May 2009 Accepted 30 July 2009 Recommended by Juan I. Godino-Llorente Two distinct two-class pattern recognition problems are studied namely the detection of male subjects who are diagnosed with vocal fold paralysis against male subjects who are diagnosed as normal and the detection of female subjects who are suffering from vocal fold edema against female subjects who do not suffer from any voice pathology. To do so utterances of the sustained vowel ah are employed from the Massachusetts Eye and Ear Infirmary database of disordered speech. Linear prediction coefficients extracted from the aforementioned utterances are used as features. The receiver operating characteristic curve of the linear classifier that stems from the Bayes classifier when Gaussian class conditional probability density functions with equal covariance matrices are assumed is derived. The optimal operating point of the linear classifier is specified with and without reject option. First results using utterances of the rainbow passage are also reported for completeness. The reject option is shown to yield statistically significant improvements in the accuracy of detecting the voice pathologies under study. Copyright 2009 C. Kotropoulos and G. R. Arce. This is an open access article distributed under the Creative Commons Attribution License which permits .