Improved consonant–vowel recognition for low bit‐rate coded speech

In this paper, we proposed a method for improving the recognition performance of 145 prominent consonant–vowel (CV) units in Indian languages for low bit‐rate coded speech. Proposed CV recognition method is carried out in two levels to reduce the similarity among a large number of CV classes. In the first level, vowel category of CV unit will be recognized, and in the second level, consonant category will be recognized. At each level of the proposed method, complementary evidences from support vector machine and hidden Markov models are combined to enhance the recognition performance. Effectiveness of the proposed two‐level CV recognition method is demonstrated by performing the recognition of isolated CV units and CV units collected from the Telugu broadcast news database. In this work, vowel onset point (VOP) is used as an anchor point for extracting accurate features from the CV unit. Therefore, a method is proposed for accurate detection of VOP in clean and coded speech. The proposed VOP detection method is based on the spectral energy in 500–2500 Hz frequency band of the speech segments present in the glottal closure region. Speech coders considered in this work are GSM full rate (ETSI 06.10), CELP (FS‐1016), and MELP (TI 2.4 kbps). Significant improvement in CV recognition performance is achieved using the proposed two‐level method compared with the existing methods under both clean and coded conditions. Copyright © 2011 John Wiley & Sons, Ltd.