Detecting Topic-Oriented Speaker Stance in Conversational Speech

Catherine Lai, Beatrice Alex, Johanna D. Moore, Leimin Tian, Tatsuro Hori, Gianpiero Francesca

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

Abstract / Description of output

Being able to detect topics and speaker stances in conversations is a key requirement for developing spoken language understanding systems that are personalized and adaptive. In this work, we explore how topic-oriented speaker stance is expressed in conversational speech. To do this, we present a new set of topic and stance annotations of the CallHome corpus of spontaneous dialogues. Specifically, we focus on six stances—positivity, certainty, surprise, amusement, interest, and comfort—which are useful for characterizing important aspects of a conversation, such as whether a conversation is going well or not. Based on this, we investigate the use of neural network models for automatically detecting speaker stance from speech in multi-turn, multi-speaker contexts. In particular, we examine how performance changes depending on how input feature representations are constructed and how this is related to dialogue structure. Our experiments show that incorporating both lexical and acoustic features is beneficial for stance detection. However, we observe variation in whether using hierarchical models for encoding lexical and acoustic information improves performance, suggesting that some aspects of speaker stance are expressed more locally than others. Overall, our findings highlight the importance of modelling interaction dynamics and non-lexical content for stance detection.
Original languageEnglish
Title of host publicationProceedings of Interspeech 2019
PublisherInternational Speech Communication Association
Number of pages5
Publication statusPublished - 19 Sept 2019
EventInterspeech 2019 - Graz, Austria
Duration: 15 Sept 201919 Sept 2019

Publication series

PublisherInternational Speech Communication Association
ISSN (Electronic)1990-9772


ConferenceInterspeech 2019
Internet address

Keywords / Materials (for Non-textual outputs)

  • spoken language understanding
  • affective computing
  • stance
  • computational paralinguistics
  • spoken dialogue


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