Interaction style detection based on Fused Cross-Correlation Model in spoken conversation

Wen Li Wei, Chung-Hsien Wu, Jen Chun Lin, Han Li

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

1 Citation (Scopus)

Abstract

In recent years, much attention has been given to dialogue strategy design to achieve intelligent speech-based human-computer interaction. Since speakers generally express their intents in different Interaction Styles (ISs), the responses of a spoken dialogue system should be versatile instead of invariable and planned. This paper presents an approach to automatic detection of a user's IS using a Fused Cross-Correlation Model (FCCM). As IS generally involves high level psychological meaning, cross-correlation among various psychological factors including emotion, personality trait, and IS is thus considered for IS detection modeling. The Bayes' theorem is then used to integrate the cross-correlation into the IS detector for enhancing the IS detection accuracy. Experiments show a promising result of the proposed approach.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages8495-8499
Number of pages5
DOIs
Publication statusPublished - 2013 Oct 18
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: 2013 May 262013 May 31

Publication series

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

Other

Other2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
CountryCanada
CityVancouver, BC
Period13-05-2613-05-31

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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