K-means nearest neighbor classifier for voice pathology

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Citations (Scopus)


The noninvasive acoustical analysis of normal and pathological voices help speech specialists to perform accurate diagnose of diseases. Pathological voices show higher vocal noise level due to malfunctioning of vocal cords. Addition of noise component in speech has found to change the spectral properties. In this study, we show the use of energy spectrum which is obtained from 21-channel filter-bank outputs, for the classification of pathological voices. A simple k-means nearest neighbor classifier based on spectral distance is designed and a good classification results have been reported.

Original languageEnglish
Title of host publicationProceedings of the IEEE INDICON 2004 - 1st India Annual Conference
Number of pages3
Publication statusPublished - 2004
EventIEEE INDICON 2004 - 1st India Annual Conference - Kharagpur, India
Duration: 20-12-200422-12-2004


ConferenceIEEE INDICON 2004 - 1st India Annual Conference

All Science Journal Classification (ASJC) codes

  • Engineering(all)


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