A large class of problems requires real-time processing of complex temporal inputs in real-time. These are difficult tasks for state-of-the-art techniques, since they require captu...
Igal Raichelgauz, Karina Odinaev, Yehoshua Y. Zeev...
The objective in any pattern recognition problem is to capture the characteristics common to each class from feature vectors of the training data. While Gaussian mixture models ap...
The use of speaker adaptation transforms as features for speaker recognition is an appealing alternative to conventional short-term cepstral features. In general, this kind of met...
In this paper, we present a novel technique for modeling the posterior probability estimates obtained from a neural network directly in the HMM framework using the Dirichlet Mixtu...
Balakrishnan Varadarajan, Garimella S. V. S. Sivar...
Abstract. In this work we propose a new method to create neural network ensembles. Our methodology develops over the conventional technique of bagging, where multiple classifiers ...