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» A Spectral Algorithm for Learning Hidden Markov Models
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CVPR
2007
IEEE
14 years 2 months ago
Multiple Target Tracking Using Spatio-Temporal Markov Chain Monte Carlo Data Association
We propose a framework for general multiple target tracking, where the input is a set of candidate regions in each frame, as obtained from a state of the art background learning, ...
Qian Yu, Gérard G. Medioni, Isaac Cohen
ICASSP
2010
IEEE
13 years 5 months ago
Model-based dereverberation in the logmelspec domain for robust distant-talking speech recognition
The REMOS (REverberation MOdeling for Speech recognition) concept for reverberation-robust distant-talking speech recognition, introduced in [1] for melspectral features, is exten...
Armin Sehr, Roland Maas, Walter Kellermann
INTERSPEECH
2010
13 years 2 months ago
HMM-based text-to-articulatory-movement prediction and analysis of critical articulators
In this paper we present a method to predict the movement of a speaker's mouth from text input using hidden Markov models (HMM). We have used a corpus of human articulatory m...
Zhen-Hua Ling, Korin Richmond, Junichi Yamagishi
ICPR
2008
IEEE
14 years 2 months ago
Face super-resolution using 8-connected Markov Random Fields with embedded prior
In patch based face super-resolution method, the patch size is usually very small, and neighbor patches’ relationship via overlapped regions is only to keep smoothness of recons...
Kai Guo, Xiaokang Yang, Rui Zhang, Guangtao Zhai, ...
JMLR
2012
11 years 10 months ago
Age-Layered Expectation Maximization for Parameter Learning in Bayesian Networks
The expectation maximization (EM) algorithm is a popular algorithm for parameter estimation in models with hidden variables. However, the algorithm has several non-trivial limitat...
Avneesh Singh Saluja, Priya Krishnan Sundararajan,...