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» Subspace Gaussian Mixture Models for speech recognition
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CSL
2004
Springer
14 years 9 months ago
Factor analysed hidden Markov models for speech recognition
Recently various techniques to improve the correlation model of feature vector elements in speech recognition systems have been proposed. Such techniques include semi-tied covaria...
Antti-Veikko I. Rosti, M. J. F. Gales
ICASSP
2011
IEEE
14 years 1 months ago
Dirichlet Mixture Models of neural net posteriors for HMM-based speech recognition
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...
TASLP
2010
117views more  TASLP 2010»
14 years 4 months ago
Speech Enhancement Using Gaussian Scale Mixture Models
This paper presents a novel probabilistic approach to speech enhancement. Instead of a deterministic logarithmic relationship, we assume a probabilistic relationship between the fr...
Jiucang Hao, Te-Won Lee, Terrence J. Sejnowski
56
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ICASSP
2009
IEEE
15 years 4 months ago
Bounded conditional mean imputation with Gaussian mixture models: A reconstruction approach to partly occluded features
In this work we show how conditional mean imputation can be bounded through the use of box-truncated Gaussian distributions. That is of interest when signals or features are partl...
Friedrich Faubel, John W. McDonough, Dietrich Klak...
INTERSPEECH
2010
14 years 4 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