Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Robustness in Automatic Speech Recognition: Fundamentals and Applications
Robustness in Automatic Speech Recognition: Fundamentals and Applications
The SMV algorithm selected by TIA and 3GPP2 for CDMA applications
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 200. on IEEE International Conference - Volume 02
Noise Robust Voice Activity Detection Based on Switching Kalman Filter
IEICE - Transactions on Information and Systems
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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.