Accent Recognition System Using Deep Belief Networks for Telugu Speech Signals

Accent and Emotion recognition for speech has become most important research area because of the increased demand of speech processing systems in handheld devices. Most of the research in speech processing is done for the English language only. In this paper, we present accent recognition system for Telugu speeches. Three important accents of Telugu were chosen and text-dependent speeches of Coastal Andhra, Rayalaseema, and Telangana accents were collected. Features like tonal power ratio, spectral flux, pitch chroma, and MFCC were extracted from these speeches. deep belief networks are used for the classification purpose. The recognition accuracy obtained in this work is 93%.

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