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EURASIP Journal on Audio, Speech, and Music Processing

, 2009:965436

First Online: 09 September 2009Received: 09 October 2008Revised: 24 February 2009Accepted: 24 June 2009

Abstract

The paper presents an adaptive system for Voiced-Unvoiced V-UV speech detection in the presence of background noise. Genetic algorithms were used to select the features that offer the best V-UV detection according to the output of a background Noise Classifier NC and a Signal-to-Noise Ratio Estimation SNRE system. The system was implemented, and the tests performed using the TIMIT speech corpus and its phonetic classification. The results were compared with a nonadaptive classification system and the V-UV detectors adopted by two important speech coding standards: the V-UV detection system in the ETSI ES 202 212 v1.1.2 and the speech classification in the Selectable Mode Vocoder SMV algorithm. In all cases the proposed adaptive V-UV classifier outperforms the traditional solutions giving an improvement of 25% in very noisy environments.

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Autor: F Beritelli - S Casale - A Russo - S Serrano

Fuente: https://link.springer.com/



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