Using artificial neural network For robust voice activity detection under adverse conditions

2009 IEEE-RIVF International Conference on Computing and Communication Technologies: Research, Innovation and Vision for the Future, RIVF 2009

Volumn , Issue , 2009, Pages

  Pham, Tuan V ^a   Tang, Chien T ^a   Stadtschnitzer, Michael ^b  

^a University of Technology   (United States)

^b GRAZ UNIVERSITY OF TECHNOLOGY   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL NEURAL NETWORK; DEVELOPED MODEL; EMPIRICAL RESULTS; HARSH ENVIRONMENT; MEL-FREQUENCY CEPSTRAL COEFFICIENTS; MODEL-BASED; NEURAL NETWORK CLASSIFIER; NEURAL NETWORK TRAINING; NOISY SPEECH; OPTIMIZATION PROCEDURES; RECENT STATE; RELIABLE MODELS; VOICE ACTIVITY DETECTION;

BACKPROPAGATION; COMPUTER SCIENCE; NETWORK PERFORMANCE; SIGNAL TO NOISE RATIO; SPEECH RECOGNITION; SYSTEMS ENGINEERING;

NEURAL NETWORKS;

EID: 71049181730     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/RIVF.2009.5174662     Document Type: Conference Paper

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