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83
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CORR
2010
Springer
95views Education» more  CORR 2010»
15 years 22 days ago
Statistical Compressive Sensing of Gaussian Mixture Models
A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical dist...
Guoshen Yu, Guillermo Sapiro
SPEECH
2008
124views more  SPEECH 2008»
15 years 17 days ago
Statistical mapping between articulatory movements and acoustic spectrum using a Gaussian mixture model
In this paper, we describe a statistical approach to both an articulatory-to-acoustic mapping and an acoustic-to-articulatory inversion mapping without using phonetic information....
Tomoki Toda, Alan W. Black, Keiichi Tokuda
124
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ICMCS
2009
IEEE
189views Multimedia» more  ICMCS 2009»
14 years 10 months ago
Emotion recognition from speech VIA boosted Gaussian mixture models
Gaussian mixture models (GMMs) and the minimum error rate classifier (i.e. Bayesian optimal classifier) are popular and effective tools for speech emotion recognition. Typically, ...
Hao Tang, Stephen M. Chu, Mark Hasegawa-Johnson, T...
INTERSPEECH
2010
14 years 7 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
111
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SAC
2010
ACM
14 years 7 months ago
Probabilistic relabelling strategies for the label switching problem in Bayesian mixture models
The label switching problem is caused by the likelihood of a Bayesian mixture model being invariant to permutations of the labels. The permutation can change multiple times betwee...
M. Sperrin, Thomas Jaki, E. Wit