A convex model for linguistic influence in group conversations

Kan Kawabata, Visar Berisha, Anna Scaglione, Amy LaCross

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations

Abstract

Conversational partners can influence each other's speaking patterns. In this paper, we aim to develop a computational model that infers influence levels directly from language samples. We propose a new approach to modeling linguistic influence in conversations based on a well-accepted model of social influence. Very generally, this approach assumes that an individual's language model can be expressed as a convex combination of language models from individuals with whom that person interacts. We propose an optimization criterion to estimate the pairwise influence between conversational partners directly from speech and language data. We evaluate the model on three different corpora: (1) a synthetic corpus where the language influence is experimentally set; (2) a corpus that tracks a child's interaction with her family during the early stages of language development; (3) a corpus of Supreme Court cases analyzing interactions between judges and attorneys.

Original languageEnglish (US)
Pages (from-to)1442-1446
Number of pages5
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Volume08-12-September-2016
DOIs
StatePublished - 2016
Event17th Annual Conference of the International Speech Communication Association, INTERSPEECH 2016 - San Francisco, United States
Duration: Sep 8 2016Sep 16 2016

Keywords

  • Communication accommodation
  • Convex modeling
  • De Groot's model
  • Language accommodation
  • Linguistic influence
  • Social influence

ASJC Scopus subject areas

  • Language and Linguistics
  • Human-Computer Interaction
  • Signal Processing
  • Software
  • Modeling and Simulation

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