Speech, Voice, Text, and Meaning: A Multidisciplinary Approach to Interview Data through the use of digital tools

Arjan Van Hessen, Silvia Calamai, Henk Van Den Heuvel, Stefania Scagliola, Norah Karrouche, Jeannine Beeken, Louise Corti, Christoph Draxler

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Interview data is multimodal data: it consists of speech sound, facial expression and gestures, captured in a particular situation, and containing textual information and emotion. This workshop shows how a multidisciplinary approach may exploit the full potential of interview data. The workshop first gives a systematic overview of the research fields working with interview data. It then presents the speech technology currently available to support transcribing and annotating interview data, such as automatic speech recognition, speaker diarization, and emotion detection. Finally, scholars who work with interview data and tools may present their work and discover how to make use of existing technology.

Original languageEnglish
Title of host publicationICMI 2020 - Proceedings of the 2020 International Conference on Multimodal Interaction
PublisherAssociation for Computing Machinery (ACM)
Pages886-887
Number of pages2
ISBN (Electronic)9781450375818
DOIs
Publication statusPublished - 21 Oct 2020
Event22nd ACM International Conference on Multimodal Interaction, ICMI 2020 - Online, Virtual, Online, Netherlands
Duration: 25 Oct 202029 Oct 2020
Conference number: 22
http://icmi.acm.org/2020/

Conference

Conference22nd ACM International Conference on Multimodal Interaction, ICMI 2020
Abbreviated titleICMI
Country/TerritoryNetherlands
CityVirtual, Online
Period25/10/2029/10/20
Internet address

Keywords

  • annotation
  • emotion detection
  • interview data
  • nlp
  • speech processing
  • transcription

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