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Applicational Areas of MFCC

Preeti Kapoor, Narina Thakur

Abstract


Mel Frequency Cepstral Coefficient is a very common and capable technique for signal processing. It is the basic method used for extracting the features of the voice signal .It is a powerful and popular acoustic vector that is used to represent and recognize the voice features and characteristics of the speaker. Mel-frequency cepstral coefficients are the coefficients that collectively represent the short-term power spectrum of a sound, based on a linear cosine transform of a log power spectrum on a nonlinear mel scale of frequency. In this paper, we study about the various applications of MFCCs. The methods which were briefly studied include Vector Quantization (VQ), K Nearest Nieghbor (KNN), Dynamic Time Wrapping (DTW), Multi-Layered Perceptron (MLP), Gaussian Mixture Model (GMM), Support Vector Machine (SVM), Hidden Markov Model.


Keywords


Mel-Frequency Cepstral Coefficient, Speech Recognition Applications, Speaker Recognition Applications, Medical Applications, Clustering Classifiers

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