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NAACL
2003
13 years 7 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
ICASSP
2011
IEEE
12 years 10 months ago
A study of the effect of emotional state upon text-independent speaker identification
In this paper we evaluate the effect of the emotional state of a speaker when text-independent speaker identification is performed. The spectral features used for speaker recogni...
Marius Vasile Ghiurcau, Corneliu Rusu, Jaakko Asto...
ICASSP
2011
IEEE
12 years 10 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»
13 years 29 days 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
ICASSP
2011
IEEE
12 years 10 months ago
Large vocabulary continuous speech recognition with context-dependent DBN-HMMS
The context-independent deep belief network (DBN) hidden Markov model (HMM) hybrid architecture has recently achieved promising results for phone recognition. In this work, we pro...
George E. Dahl, Dong Yu, Li Deng, Alex Acero