Spoken Indian Language Classification using GMM supervectors and Artificial Neural Networks

Published: Jul 1, 2019
Abstract
Indian languages are phonetic in nature; phonetics is branch of linguistics which studies the structure of human language sound. Acoustic phonetic features associated with languages play an important role in spoken language identification. In this paper, Gaussian Mixture Model supervectors is used to capture acoustic phonetic variation in Indian languages. Mel frequency cepstral coefficient (MFCC) with delta coefficients is used to represent the...
Paper Details
Title
Spoken Indian Language Classification using GMM supervectors and Artificial Neural Networks
Published Date
Jul 1, 2019
Journal
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