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ECML
2006
Springer
15 years 1 months ago
Deconvolutive Clustering of Markov States
In this paper we formulate the problem of grouping the states of a discrete Markov chain of arbitrary order simultaneously with deconvolving its transition probabilities. As the na...
Ata Kabán, Xin Wang
KDD
2008
ACM
115views Data Mining» more  KDD 2008»
15 years 10 months ago
SPIRAL: efficient and exact model identification for hidden Markov models
Hidden Markov models (HMMs) have received considerable attention in various communities (e.g, speech recognition, neurology and bioinformatic) since many applications that use HMM...
Yasuhiro Fujiwara, Yasushi Sakurai, Masashi Yamamu...
64
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ICIP
2003
IEEE
15 years 11 months ago
Audio-visual speaker identification using coupled hidden Markov models
In this paper, we investigate the use of the coupled hidden Markov models (CHMM) for the task of audio-visual text dependent speaker identification. Our system determines the iden...
Tieyan Fu, Xiao Xing Liu, Lu Hong Liang, Xiaobo Pi...
ECML
2007
Springer
15 years 3 months ago
Separating Precision and Mean in Dirichlet-Enhanced High-Order Markov Models
Abstract. Robustly estimating the state-transition probabilities of highorder Markov processes is an essential task in many applications such as natural language modeling or protei...
Rikiya Takahashi
ALMOB
2006
80views more  ALMOB 2006»
14 years 9 months ago
Effective p-value computations using Finite Markov Chain Imbedding (FMCI): application to local score and to pattern statistics
The technique of Finite Markov Chain Imbedding (FMCI) is a classical approach to complex combinatorial problems related to sequences. In order to get efficient algorithms, it is k...
Grégory Nuel