The nature of statistical learning theory
The nature of statistical learning theory
Using analytic QP and sparseness to speed training of support vector machines
Proceedings of the 1998 conference on Advances in neural information processing systems II
Speech Coding Algorithms: Foundation and Evolution of Standardized Coders
Speech Coding Algorithms: Foundation and Evolution of Standardized Coders
ETSI AMR-2 VAD: evaluation and ultra low-resource implementation
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
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In the paper we demonstrate a complex supervised learning method based on a binary decision graphs This method is employed in construction of a silence/speech detector Performance of the resulting silence/speech detector is compared with performance of common silence/speech detectors used in telecommunications and with a detector based on HMM and a bigram silence/speech language model Each non-leaf node of a decision graph has assigned a question and a sub-classifier answering this question We test three kinds of these sub-classifiers: linear classifier, classifier based on separating quadratic hyper-plane (SQHP), and Support Vector Machines (SVM) based classifier Moreover, besides usage of a single decision graph we investigate application of a set of binary decision graphs.