Support Vector Machine Classification of Stress Types in Speech
Journal Title: IOSR journal of VLSI and Signal Processing - Year 2018, Vol 8, Issue 2
Abstract
Speech of human beings is the reflection of the state of mind. Proper evaluation of these speech signals into stress types is necessary in order to ensure that the person is in a healthy state of mind. In this work we propose a SVM classifier for speech stress classification algorithm, with sophisticated feature extraction techniques as Mel Frequency Cepstral Coefficients (MFCC). The SVM algorithm assists the system to learn the speech patterns in real time and self-train itself in order to improve the classification accuracy of the overall system. The proposed system is suitable for real time speech and is language and word independent.
Authors and Affiliations
Mrs. N. P. Dhole1 ,, Dr. S. N. Kale2
Keywords
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