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» A Spectral Algorithm for Learning Hidden Markov Models
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AUTOMATICA
2007
82views more  AUTOMATICA 2007»
13 years 7 months ago
Simulation-based optimal sensor scheduling with application to observer trajectory planning
The sensor scheduling problem can be formulated as a controlled hidden Markov model and this paper solves the problem when the state, observation and action spaces are continuous....
Sumeetpal S. Singh, Nikolaos Kantas, Ba-Ngu Vo, Ar...
AAAI
2006
13 years 9 months ago
Fast Hierarchical Goal Schema Recognition
We present our work on using statistical, corpus-based machine learning techniques to simultaneously recognize an agent's current goal schemas at various levels of a hierarch...
Nate Blaylock, James F. Allen
TASLP
2008
154views more  TASLP 2008»
13 years 7 months ago
Capturing Local Variability for Speaker Normalization in Speech Recognition
The new model reduces the impact of local spectral and temporal variability by estimating a finite set of spectral and temporal warping factors which are applied to speech at the f...
Antonio Miguel, Eduardo Lleida, Richard Rose, Luis...
ACSC
2004
IEEE
13 years 11 months ago
Learning Models for English Speech Recognition
This paper reports on an experiment to determine the optimal parameters for a speech recogniser that is part of a computer aided instruction system for assisting learners of Engli...
Huayang Xie, Peter Andreae, Mengjie Zhang, Paul Wa...
IDEAL
2004
Springer
14 years 1 months ago
Stock Trading by Modelling Price Trend with Dynamic Bayesian Networks
We study a stock trading method based on dynamic bayesian networks to model the dynamics of the trend of stock prices. We design a three level hierarchical hidden Markov model (HHM...
Jangmin O, Jae Won Lee, Sung-Bae Park, Byoung-Tak ...