Adaptive V/UV Speech Detection Based on Characterization of Background Noise. (9th September 2009)

• Record Type: Journal Article
• Authors: Beritelli, F.; Casale, S.; Russo, A.; Serrano, S.
• Other Names: Rigoll Gerhard Academic Editor.
• Is Part Of: EURASIP journal on audio, speech, and music processing. Volume 2009(2009)
• Publication Date: 2009-09-09
• Subjects: Sound -- Recording and reproducing -- Digital techniques -- Periodicals; Computer sound processing -- Periodicals; Computer sound processing; Sound -- Recording and reproducing -- Digital techniques; Periodicals; Electronic journal; Electronic journals; 620.2
• DOI: 10.1155/2009/965436
• Languages: English
• ISSNs: 1687-4714

Abstract

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.