Suman Senapati

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Pre-processing of Speech Signal serves various purposes in any speech processing application. Out of these, silence/unvoiced portion removal along with endpoint detection is the fundamental step for applications like Speech and Speaker Recognition. The proposed method uses Probability Density Function (PDF) of the background noise and a Linear Pattern(More)
Accurate detection of dialogue acts is essential for understanding human conversations and to recognize emotions. This requires 1) the segmentation of human-human dialogs into turns, 2) the intra-turn segmentation into DA boundaries and 3) the classification of each segment according to a DA tag. Most dialogue act classification models approaches the(More)
In this article a method of computing similarity of two Chinese pop songs is presented. It is based on five attributes extracted from the audio signal. They include music instrument, singing voice style, singer gender, tempo, and degree of noisiness. We compare the computed similarity measures with similarity scores obtained with subjective listening by(More)
— Automatic Speaker recognition (ASR) is a pattern recognition problem that involves the process of automatically recognizing the speaker from their voices. Password protected speaker recognition system gives an extra security to the system where a person is not only identified by his natural voice bio-metric but also needs to remember a password (e.g. a(More)
— Speaker recognition system needs an efficient feature extraction process and an appropriate speaker model developed from these features. The key issue in robust Automatic Speaker Recognition (ASR) system is to yield good recognition accuracy regardless of the mismatch in the environmental conditions between training and testing time. The work uses(More)
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