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Discriminative Training for Multiple Observation Likelihood Ratio Based Voice Activity Detection
2010
IEEE Signal Processing Letters
It is possible to show that the likelihood ratio (LR) test from multiple observations can enhance the performance of a statically modeled voice actively detection (VAD) system. However, the combination weights for the likelihood ratios (LRs) in each observation are rather empirical and heuristical. In this study, the optimal combination weights from two discriminative training methods are studied to directly improve VAD performance, in terms of reduced misclassification errors and improved
doi:10.1109/lsp.2010.2066561
fatcat:pdicgeglgncy3kg7yega6agbmm