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ECML
2006
Springer
13 years 11 months ago
PAC-Learning of Markov Models with Hidden State
The standard approach for learning Markov Models with Hidden State uses the Expectation-Maximization framework. While this approach had a significant impact on several practical ap...
Ricard Gavaldà, Philipp W. Keller, Joelle P...
NIPS
1996
13 years 8 months ago
A Micropower Analog VLSI HMM State Decoder for Wordspotting
We describe the implementation of a hidden Markov model state decoding system, a component for a wordspotting speech recognition system. The key specification for this state decod...
John Lazzaro, John Wawrzynek, Richard Lippmann
HAPTICS
2002
IEEE
14 years 10 days ago
Building a Task Language for Segmentation and Recognition of User Input to Cooperative Manipulation Systems
We present the results of using Hidden Markov Models (HMMs) for automatic segmentation and recognition of user motions. Previous work on recognition of user intent with man/machin...
C. Sean Hundtofte, Gregory D. Hager, Allison M. Ok...
ICPR
2006
IEEE
14 years 8 months ago
Mixture of Support Vector Machines for HMM based Speech Recognition
Speech recognition is usually based on Hidden Markov Models (HMMs), which represent the temporal dynamics of speech very efficiently, and Gaussian mixture models, which do non-opt...
Sven E. Krüger, Martin Schafföner, Marce...
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