Text independent classification of normal and pathological voices using MFCCs and GMM-UBM

Abstract

This paper proposes a text independent method for the classification of normal and pathological voices. If the classifier is text dependent i.e classifier is trained for a particular phoneme, then it may difficult for the patient to pronounce the particular phoneme. To overcome this difficulty, a text independent classification method is proposed, which… (More)

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@article{Vikram2013TextIC, title={Text independent classification of normal and pathological voices using MFCCs and GMM-UBM}, author={C. M. Vikram and K. Umarani}, journal={2013 IEEE CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES}, year={2013}, pages={1215-1220} }