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ICASSP
2011
IEEE
12 years 8 months ago
Comparing multilayer perceptron to Deep Belief Network Tandem features for robust ASR
In this paper, we extend the work done on integrating multilayer perceptron (MLP) networks with HMM systems via the Tandem approach. In particular, we explore whether the use of D...
Oriol Vinyals, Suman V. Ravuri
ICASSP
2011
IEEE
12 years 8 months ago
Learning non-parametric models of pronunciation
As more data becomes available for a given speech recognition task, the natural way to improve recognition accuracy is to train larger models. But, while this strategy yields mode...
Brian Hutchinson, Jasha Droppo
ICASSP
2010
IEEE
13 years 5 months ago
Investigations on ensemble based unsupervised adaptation methods
We have previously proposed unsupervised cross-validation (CV) adaptation that introduces CV into an iterative unsupervised batch mode adaptation framework to suppress the influe...
Yu Kubota, Takahiro Shinozaki, Sadaoki Furui
ICTAI
2007
IEEE
13 years 11 months ago
Comparative Evaluation of Speech Parameterizations for Speech Recognition
In this work, we present comparative evaluation of the practical value of some recently proposed speech parameterizations on the speech recognition task. Specifically, in a common...
Iosif Mporas, Todor Ganchev, Mihalis Siafarikas, T...
ICPR
2008
IEEE
14 years 6 months ago
A phone-viseme dynamic Bayesian network for audio-visual automatic speech recognition
This work extends and improves a recently introduced (Dec. 2007) dynamic Bayesian network (DBN) based audio-visual automatic speech recognition (AVASR) system. That system models ...
Louis H. Terry, Aggelos K. Katsaggelos
ICIP
2002
IEEE
14 years 6 months ago
Application of support vector machines classifiers to visual speech recognition
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...
Mihaela Gordan, Constantine Kotropoulos, Apostolos...