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ICMCS
2009
IEEE
189views Multimedia» more  ICMCS 2009»
13 years 6 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...
TASLP
2011
13 years 4 months ago
Predicting Preference Judgments of Individual Normal and Hearing-Impaired Listeners With Gaussian Processes
Abstract—A probabilistic kernel approach to pairwise preference learning based on Gaussian processes is applied to predict preference judgments for sound quality degradation mech...
Perry Groot, Tom Heskes, Tjeerd Dijkstra, James M....
TCSV
2011
13 years 4 months ago
Mixture of Gaussians-Based Background Subtraction for Bayer-Pattern Image Sequences
This paper proposes a background subtraction method for Bayer-pattern image sequences. The proposed method models the background in a Bayer-pattern domain using a mixture of Gauss...
Jae Kyu Suhr, Ho Gi Jung, Gen Li, Jaihie Kim
INTERSPEECH
2010
13 years 3 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
JMLR
2010
194views more  JMLR 2010»
13 years 3 months ago
Graphical Gaussian modelling of multivariate time series with latent variables
In time series analysis, inference about causeeffect relationships among multiple times series is commonly based on the concept of Granger causality, which exploits temporal struc...
Michael Eichler