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ICASSP
2011
IEEE
12 years 8 months ago
Structured precision modelling with Cholesky Basis Superposition for speech recognition
Structured precision modelling is an important approach to improve the intra-frame correlation modelling of the standard HMM, where Gaussian mixture model with diagonal covariance...
Lei Jia, Kai Yu, Bo Xu
INTERSPEECH
2010
12 years 11 months ago
Boosted mixture learning of Gaussian mixture HMMs for speech recognition
In this paper, we propose a novel boosted mixture learning (BML) framework for Gaussian mixture HMMs in speech recognition. BML is an incremental method to learn mixture models fo...
Jun Du, Yu Hu, Hui Jiang
ICPR
2006
IEEE
14 years 6 months ago
A Hybrid HMM-Based Speech Recognizer Using Kernel-Based Discriminants as Acoustic Models
In this paper we propose a novel order-recursive training algorithm for kernel-based discriminants which is computationally efficient. We integrate this method in a hybrid HMM-bas...
Edin Andelic, Marcel Katz, Martin Schafföner,...
INTERSPEECH
2010
12 years 11 months ago
Canonical state models for automatic speech recognition
Current speech recognition systems are often based on HMMs with state-clustered Gaussian Mixture Models (GMMs) to represent the context dependent output distributions. Though high...
Mark J. F. Gales, Kai Yu
ICPR
2004
IEEE
14 years 6 months ago
Bayesian Face Recognition Based on Gaussian Mixture Models
Bayesian analysis is a popular subspace based face recognition method. It casts the face recognition task into a binary classification problem with each of the two classes, intrap...
Xiaogang Wang, Xiaoou Tang