Marginalized Viterbi Algorithm for Hierarchical Hidden Markov Models

URI http://harp.lib.hiroshima-u.ac.jp/hiroshima-cu/metadata/12386
ファイル
タイトル
Marginalized Viterbi Algorithm for Hierarchical Hidden Markov Models
著者
氏名 HAYASHI Akira
ヨミ ハヤシ アキラ
別名 林 朗
氏名 IWATA Kazunori
ヨミ イワタ カズノリ
別名 岩田 一貴
氏名 SUEMATSU Nobuo
ヨミ スエマツ ノブオ
別名 末松  伸朗
キーワード
Time series data
Hierarchical HMM
Finding the most likely state sequence
Generalized Viterbi algorithm
Marginalized Viterbi algorithm
抄録

The generalized Viterbi algorithm, a direct extension of the Viterbi algorithm for hidden Markov models (HMMs), has been used to find the most likely state sequence for hierarchical HMMs. However, the generalized Viterbi algorithm finds the most likely whole level state sequence rather than the most likely upper level state sequence. In this paper, we propose a marginalized Viterbi algorithm, which finds the most likely upper level state sequence by marginalizing lower level state sequences. We show experimentally that the marginalized Viterbi algorithm is more accurate than the generalized Viterbi algorithm in terms of upper level state sequence estimation.

査読の有無
掲載雑誌名
Pattern Recognition
46
12
開始ページ
3452
終了ページ
3459
出版年月日
2013-12
出版者
Elsevier
ISSN
00313203
NCID
AA00770025
AA11948832
DOI
10.1016/j.patcog.2013.06.001
本文言語
英語
資料タイプ
学術雑誌論文
著者版フラグ
著者版
権利情報
@ 2013 Published by Elsevier Ltd.
This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
関連URL
旧URI
区分
hiroshima-cu