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  • Research Article
  • Open Access

Adaptive V/UV Speech Detection Based on Characterization of Background Noise

EURASIP Journal on Audio, Speech, and Music Processing20092009:965436

  • Received: 9 October 2008
  • Accepted: 24 June 2009
  • Published:


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.


  • Genetic Algorithm
  • Background Noise
  • Acoustics
  • Ratio Estimation
  • Adaptive System

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Authors’ Affiliations

Dipartimento di Ingegneria Informatica e delle Telecomunicazioni, Universita' degli Studi di Catania, Viale Andrea Doria, 6, 95125 Catania, Italy
Dipartimento di Fisica della Materia e Ingegneria Elettronica, Universita' di Messina, Salita Sperone, 31, 98166 Messina, Italy


© F. Beritelli et al. 2009

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.