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» Learning a language model from continuous speech
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JAIR
2010
181views more  JAIR 2010»
14 years 4 months ago
Intrusion Detection using Continuous Time Bayesian Networks
Intrusion detection systems (IDSs) fall into two high-level categories: network-based systems (NIDS) that monitor network behaviors, and host-based systems (HIDS) that monitor sys...
Jing Xu, Christian R. Shelton
ISM
2005
IEEE
132views Multimedia» more  ISM 2005»
15 years 3 months ago
A Pitch-Based Rapid Speech Segmentation for Speaker Indexing
Segmentation of continuous audio is important for speaker indexing. The reliability of models in speaker indexing depends much on segmentation. Commonly used method is based on th...
Min Yang, Yingchun Yang, Zhaohui Wu
NIPS
2001
14 years 11 months ago
Sequential Noise Compensation by Sequential Monte Carlo Method
We present a sequential Monte Carlo method applied to additive noise compensation for robust speech recognition in time-varying noise. The method generates a set of samples accord...
K. Yao, S. Nakamura
AIED
2009
Springer
15 years 4 months ago
Discovering Tutorial Dialogue Strategies with Hidden Markov Models
Identifying effective tutorial strategies is a key problem for tutorial dialogue systems research. Ongoing work in human-human tutorial dialogue continues to reveal the complex phe...
Kristy Elizabeth Boyer, Eunyoung Ha, Michael D. Wa...
FLAIRS
2008
15 years 6 days ago
Learning Dynamic Naive Bayesian Classifiers
Hidden Markov models are a powerful technique to model and classify temporal sequences, such as in speech and gesture recognition. However, defining these models is still an art: ...
Miriam Martínez, Luis Enrique Sucar