Influence relation estimation based on lexical entrainment in conversation

Tomoharu Iwata*, Shinji Watanabe

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


In conversations, people tend to mimic their companions' behavior depending on their level of trust. This phenomenon is known as entrainment. We propose a probabilistic model for estimating influences among speakers from conversation data involving multiple people by modeling lexical entrainment. The proposed model estimates word use as a function of the weighted sum of the earlier word use of other speakers. The weights represent influences between speakers. The influences can be efficiently estimated by using the expectation maximization (EM) algorithm. We also develop its online inference procedures for sequentially modeling the dynamics of influence relations. Experiments performed on two meeting data sets one in Japanese and one in English demonstrate the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)329-339
Number of pages11
JournalSpeech Communication
Issue number2
Publication statusPublished - 2013 Feb
Externally publishedYes


  • Conversation analysis
  • Entrainment
  • Influence
  • Latent variable model

ASJC Scopus subject areas

  • Software
  • Modelling and Simulation
  • Communication
  • Language and Linguistics
  • Linguistics and Language
  • Computer Vision and Pattern Recognition
  • Computer Science Applications


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