Overlapped State Hidden Semi-Markov Model for Grouped Multiple Sequences

Hiromi Narimatsu, Hiroyuki Kasai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Efficient analysis of multiple sequential data is becoming necessary for identifying sequential patterns of multiple objects of interest. This analysis has major practical and technical importance because finding such patterns necessitates extraction and discovery of latent but meaningful groups of sequences from apparently extraneous but mutually interrelated multiple sequences. However, conventional sequential data analysis methods have not specifically examined this particular technical direction. To tackle this challenge, we propose a new model designated as overlapped state hidden semi-Markov model (OS-HSMM). The model represents the lengths of intervals and overlap among multiple events that are semantically interpretable and appearing across multiple sequences. The salient contribution is that OS-HSMM represents the overlap of two states by extending the state duration probability in HSMM to allow a negative value. Consequently, it handles the state interval and the state overlap simultaneously. Results of our evaluations underscore the effectiveness of our model.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3397-3401
Number of pages5
ISBN (Electronic)9781509066315
DOIs
Publication statusPublished - 2020 May
Event2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Barcelona, Spain
Duration: 2020 May 42020 May 8

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2020-May
ISSN (Print)1520-6149

Conference

Conference2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
CountrySpain
CityBarcelona
Period20/5/420/5/8

Keywords

  • Grouped sequences
  • hidden semi-Markov model
  • multiple sequential data analysis
  • overlapped state

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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