Title :
Acoustic Speech Analysis for Hypernasality Detection in Children
Author :
Castellanos, G. ; Daza, G. ; Sanchez, L. ; Castrillon, O. ; Suarez, J.
Author_Institution :
Univ. Nacional de Colombia Sede Manizales, Columbia, SC
fDate :
Aug. 30 2006-Sept. 3 2006
Abstract :
Here, an analysis of different acoustic features and their influence in automatic identification of hypernasality is shown. Effective feature selection method includes preprocessing of the initial feature space based on statistical independence analysis. Simultaneously, the synthesis of a specialized diagnostic feature is proposed based on analyzing the acoustic emission of the hyper nasal speech. As a result, It is obtained the acoustic features can differentiate with enough precision the pathology. However, the proposed feature does not require training samples and less computational power, as well
Keywords :
paediatrics; speech processing; statistical analysis; acoustic emission analysis; acoustic speech analysis; automatic identification; children; feature selection method; hypernasal speech; hypernasality detection; pathology; precision; specialized diagnostic feature; statistical independence analysis; Acoustic distortion; Acoustic emission; Acoustic signal detection; Cities and towns; Pathology; Resonance; Speech analysis; Speech enhancement; Speech synthesis; Surgery;
Conference_Titel :
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location :
New York, NY
Print_ISBN :
1-4244-0032-5
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2006.260572