Consonant–Vowel Recognition in the Presence of Coding and Background Noise

Abstract

In this chapter, an approach for improving the recognition performance of CV units under clean, coded, and noisy conditions is presented. Proposed CV recognition method is carried out in two stages. In the first stage vowel category of CV unit is recognized, and in the second stage consonant category is recognized. At each stage of the proposed method, complementary evidences from support vector machine (SVM) and hidden Markov models (HMM) are combined for enhancing the recognition performance of CV units. In the proposed CV recognition approach, VOP is used as an anchor point for extracting features from the CV unit. Therefore, VOP detection methods presented in previous chapter are used for this work. Performance of the proposed CV recognition method is demonstrated under coding and noisy conditions. Recognition studies are carried out using isolated CV and CV units from Telugu broadcast news databases. Further, performance of the CV recognition system under background noise is improved by using combined temporal and spectral processing-based preprocessing methods.