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ICASSP
2008
IEEE
15 years 6 months ago
Rhetorical-State Hidden Markov Models for extractive speech summarization
We propose an extractive summarization system with a novel non-generative probabilistic framework for speech summarization. One of the most underutilized features in extractive su...
Pascale Fung, Ricky Ho Yin Chan, Justin Jian Zhang
BMCBI
2008
170views more  BMCBI 2008»
15 years 1 hour 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
TSP
2008
180views more  TSP 2008»
14 years 11 months ago
Support Vector Machine Training for Improved Hidden Markov Modeling
We present a discriminative training algorithm, that uses support vector machines (SVMs), to improve the classification of discrete and continuous output probability hidden Markov ...
Alba Sloin, David Burshtein
ICCV
2009
IEEE
6637views Computer Vision» more  ICCV 2009»
16 years 4 months ago
A Markov Clustering Topic Model for Mining Behaviour in Video
This paper addresses the problem of fully automated mining of public space video data. A novel Markov Clustering Topic Model (MCTM) is introduced which builds on existing Dynami...
Timothy Hospedales, Shaogang Gong, Tao Xiang
ICIAP
2007
ACM
16 years 5 hour ago
Sparseness Achievement in Hidden Markov Models
In this paper, a novel learning algorithm for Hidden Markov Models (HMMs) has been devised. The key issue is the achievement of a sparse model, i.e., a model in which all irreleva...
Manuele Bicego, Marco Cristani, Vittorio Murino