DocumentCode :
723324
Title :
Assessing a set of glottal features from vocal fold biomechanics for detecting vocal pathology
Author :
Lazaro Carrascosa, Carlos ; Gomez Vilda, Pedro
Author_Institution :
Univ. Rey Juan Carlos, Spain
fYear :
2015
fDate :
10-12 June 2015
Firstpage :
119
Lastpage :
126
Abstract :
This paper summarizes a statistical study of a set of glottal features with the ultimate aim of measuring their capacity to discriminate and detect vocal pathology. The study is concentrated in the analysis of relevance of a set of features obtained from the analysis of phonated speech, specifically an open vowel as /a/. The speech signal was inversely filtered to obtain the glottal source, which on its turn was used to generate a set of 72 features, describing its biometrical and biomechanical properties, among others. The study of relevance is based on factorial analysis, parametrical and non-parametrical hypothesis tests and effect size analysis, with the aim of assessing the pathologic/normophonic condition of the speaker. The validation of the results is based on discriminant analysis. The conclusions allow establishing the most relevant features and feature families for pathological voice detection. High classification rates are obtained in many cases.
Keywords :
bioacoustics; biological tissues; biomechanics; medical disorders; medical signal detection; medical signal processing; patient diagnosis; speech processing; statistical analysis; biomechanical properties; biometrical properties; discriminant analysis; effect size analysis; factorial analysis; glottal feature statistics; glottal features; glottal source; inversely filtered speech signal; nonparametric hypothesis tests; open vowel; phonated speech analysis; speaker normophonic condition; speaker pathologic condition; vocal fold biomechanics; vocal pathology detection; vocal pathology discrimination; Biomechanics; Cepstral analysis; Databases; Feature extraction; Pathology; Protocols; Speech; diagnostic support; discriminant analysis; effect size; glottal features; vocal disease;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinspired Intelligence (IWOBI), 2015 4th International Work Conference on
Conference_Location :
San Sebastian
Print_ISBN :
978-1-4673-7845-1
Type :
conf
DOI :
10.1109/IWOBI.2015.7160154
Filename :
7160154
Link To Document :
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