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ACL
2006
13 years 9 months ago
Segment-Based Hidden Markov Models for Information Extraction
Hidden Markov models (HMMs) are powerful statistical models that have found successful applications in Information Extraction (IE). In current approaches to applying HMMs to IE, a...
Zhenmei Gu, Nick Cercone
VTS
2000
IEEE
113views Hardware» more  VTS 2000»
14 years 1 hour ago
Hidden Markov and Independence Models with Patterns for Sequential BIST
We propose a novel BIST technique for non-scan sequential circuits which does not modify the circuit under test. It uses a learning algorithm to build a hardware test sequence gen...
Laurent Bréhélin, Olivier Gascuel, G...
ICPR
2010
IEEE
13 years 9 months ago
Noise-Robust Voice Activity Detector Based on Hidden Semi-Markov Models
This paper concentrates on speech duration distributions that are usually invariant to noises and proposes a noise-robust and real-time voice activity detector (VAD) using the hid...
Xianglong Liu, Yuan Liang, Yihua Lou, He Li, Baoso...
BMCBI
2008
170views more  BMCBI 2008»
13 years 7 months ago
Implementing EM and Viterbi algorithms for Hidden Markov Model in linear memory
Background: The Baum-Welch learning procedure for Hidden Markov Models (HMMs) provides a powerful tool for tailoring HMM topologies to data for use in knowledge discovery and clus...
Alexander G. Churbanov, Stephen Winters-Hilt
CORR
2006
Springer
81views Education» more  CORR 2006»
13 years 7 months ago
Universal Filtering via Hidden Markov Modeling
The problem of discrete universal filtering, in which the components of a discrete signal emitted by an unknown source and corrupted by a known discrete memoryless channel (DMC) ar...
Taesup Moon, Tsachy Weissman