Speech recognition is usually based on Hidden Markov Models (HMMs), which represent the temporal dynamics of speech very efficiently, and Gaussian mixture models, which do non-opt...
This paper proposes a unit-selection and waveform concatenation speech synthesis system based on synthetic speech naturalness evaluation. A Support Vector Machine (SVM) and Log Li...
Heng Lu 0002, Zhen-Hua Ling, Li-Rong Dai, Ren-Hua ...
Hybrid of Neural Network (NN) and Hidden Markov Model (HMM) has been popular in word recognition, taking advantage of NN discriminative property and HMM representational capabilit...
Abdul Rahim Ahmad, Christian Viard-Gaudin, Marzuki...
We show that a classifier based on Gaussian mixture models (GMM) can be trained discriminatively to improve accuracy. We describe a training procedure based on the extended Baum-W...
In this paper we proposed a visual speech recognition network based on Support Vector Machines. Each word of the dictionary is modeled by a set of temporal sequences of visemes. E...