scholarly journals Reduced-Complexity Estimation for Large-Scale Hidden Markov Models

2004 ◽  
Vol 52 (5) ◽  
pp. 1242-1249 ◽  
Author(s):  
S. Dey ◽  
I. Mareels
Keyword(s):  
Hidden Markov Models ◽  
Large Scale ◽  
Markov Models ◽  
Hidden Markov ◽  
Complexity Estimation ◽  
Reduced Complexity

scholarly journals A spark-based parallel distributed posterior decoding algorithm for big data hidden Markov models decoding problem

2021 ◽  
Vol 10 (3) ◽  
pp. 789
Author(s):  
Imad Sassi ◽  
Samir Anter ◽  
Abdelkrim Bekkhoucha
Keyword(s):  
Big Data ◽  
Hidden Markov Models ◽  
Large Scale ◽  
Markov Models ◽  
Hidden Markov ◽  
Machine Learning Algorithms ◽  
Decoding Algorithm ◽  
Large Scale Data ◽  
Large Scale Data Processing ◽  
Mapreduce Paradigm

<span lang="EN-US">Hidden </span><span lang="IN">M</span><span lang="EN-US">arkov models (HMMs) are one of machine learning algorithms which have been widely used and demonstrated their efficiency in many conventional applications. This paper proposes a modified posterior decoding algorithm to solve hidden Markov models decoding problem based on MapReduce paradigm and spark’s resilient distributed dataset (RDDs) concept, for large-scale data processing. The objective of this work is to improve the performances of HMM to deal with big data challenges. The proposed algorithm shows a great improvement in reducing time complexity and provides good results in terms of running time, speedup, and parallelization efficiency for a large amount of data, i.e., large states number and large sequences number.</span>

Estimating Personality Impression from Speech Record Using Hidden Markov Models

2015 ◽  
Vol 135 (12) ◽  
pp. 1517-1523 ◽  
Author(s):  
Yicheng Jin ◽  
Takuto Sakuma ◽  
Shohei Kato ◽  
Tsutomu Kunitachi
Keyword(s):  
Hidden Markov Models ◽  
Markov Models ◽  
Hidden Markov
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