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ECML
2006
Springer
15 years 1 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...
IJCAI
2007
14 years 11 months ago
Dynamically Weighted Hidden Markov Model for Spam Deobfuscation
Spam deobfuscation is a processing to detect obfuscated words appeared in spam emails and to convert them back to the original words for correct recognition. Lexicon tree hidden M...
Seunghak Lee, Iryoung Jeong, Seungjin Choi
PRL
2007
131views more  PRL 2007»
14 years 9 months ago
A new look at discriminative training for hidden Markov models
ct 7 Discriminative training for hidden Markov models (HMMs) has been a central theme in speech recognition research for many years. 8 One most popular technique is minimum classiï...
Xiaodong He, Li Deng
ICASSP
2011
IEEE
14 years 1 months ago
Multi-view and multi-objective semi-supervised learning for large vocabulary continuous speech recognition
Current hidden Markov acoustic modeling for large vocabulary continuous speech recognition (LVCSR) relies on the availability of abundant labeled transcriptions. Given that speech...
Xiaodong Cui, Jing Huang, Jen-Tzung Chien
ICMCS
2000
IEEE
138views Multimedia» more  ICMCS 2000»
15 years 2 months ago
Event-Coupled Hidden Markov Models
Inferences from time-series data can be greatly enhanced by taking into account multiple modalities. In some cases, such as audio of speech and the corresponding video of lip gest...
Trausti T. Kristjansson, Brendan J. Frey, Thomas S...