Abstract
Speech signal is modelled using the average energy of the signal in the zerocrossing intervals. Variation of these energies in the zerocrossing interval of the signal is studied and the distribution of this parameter through out the signal is evaluated. It is observed that the distribution patterns are similar for repeated utterances of the same vowels and varies from vowel to vowel. Credibility of the proposed parameter is verified over five Malayalam (one of the most popular Indian language) vowels using multilayer feed forward artificial neural network based recognition system. The performance of the system using additive white Gaussian noise corrupted speech is also studied for different SNR levels. From the experimental results it is evident that the average energy information in the zerocrossing intervals and its distributions can be effectively utilised for vowel phone classification and recognition.
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