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» Boosted mixture learning of Gaussian mixture HMMs for speech...
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NAACL
2003
13 years 6 months ago
Implicit Trajectory Modeling through Gaussian Transition Models for Speech Recognition
It is well known that frame independence assumption is a fundamental limitation of current HMM based speech recognition systems. By treating each speech frame independently, HMMs ...
Hua Yu, Tanja Schultz
ICML
2003
IEEE
14 years 5 months ago
Discriminative Gaussian Mixture Models: A Comparison with Kernel Classifiers
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...
Aldebaro Klautau, Nikola Jevtic, Alon Orlitsky
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
INTERSPEECH
2010
12 years 11 months ago
Bayesian speaker recognition using Gaussian mixture model and laplace approximation
This paper presents a Bayesian approach for Gaussian mixture model (GMM)-based speaker identification. Some approaches evaluate the speaker score of a test speech utterance using ...
Shih-Sian Cheng, I-Fan Chen, Hsin-Min Wang
ICASSP
2011
IEEE
12 years 8 months ago
HNM-based MFCC+F0 extractor applied to statistical speech synthesis
Currently, the statistical framework based on Hidden Markov Models (HMMs) plays a relevant role in speech synthesis, while voice conversion systems based on Gaussian Mixture Model...
Daniel Erro, Iñaki Sainz, Eva Navas, Inma H...