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171
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TSP
2010
14 years 10 months ago
A multi-resolution hidden Markov model using class-specific features
We address the problem in signal classification applications, such as automatic speech recognition (ASR) systems that employ the hidden Markov model (HMM), that it is necessary to...
Paul M. Baggenstoss
134
Voted
ECBS
2004
IEEE
129views Hardware» more  ECBS 2004»
15 years 7 months ago
Using Feature Modeling for Program Comprehension and Software Architecture Recovery
: The available evidence in a legacy software system, which can help in its understanding and recovery of its architecture are not always sufficient. Very often the system's d...
Ilian Pashov, Matthias Riebisch
143
Voted
ICCS
2009
Springer
15 years 10 months ago
Querying for Feature Extraction and Visualization in Climate Modeling
The ultimate goal of data visualization is to clearly portray features relevant to the problem being studied. This goal can be realized only if users can effectively communicate t...
C. Ryan Johnson, Markus Glatter, Wesley Kendall, J...
122
Voted
ICASSP
2011
IEEE
14 years 7 months ago
Integrating articulatory features using Kullback-Leibler divergence based acoustic model for phoneme recognition
In this paper, we propose a novel framework to integrate articulatory features (AFs) into HMM- based ASR system. This is achieved by using posterior probabilities of different AFs...
Ramya Rasipuram, Magimai.-Doss Mathew
145
Voted
LION
2010
Springer
209views Optimization» more  LION 2010»
15 years 8 months ago
Feature Extraction from Optimization Data via DataModeler's Ensemble Symbolic Regression
We demonstrate a means of knowledge discovery through feature extraction that exploits the search history of an optimization run. We regress a symbolic model ensemble from optimiza...
Kalyan Veeramachaneni, Katya Vladislavleva, Una-Ma...