The INTERSPEECH 2016 computational paralinguistics challenge: Deception, sincerity & native language

Björn Schuller, Stefan Steidl, Anton Batliner, Julia Hirschberg, Judee K Burgoon, Alice Baird, Aaron Elkins, Yue Zhang, Eduardo Coutinho, Keelan Evanini

Research output: Contribution to journalArticle

100 Scopus citations

Abstract

The INTERSPEECH 2016 Computational Paralinguistics Challenge addresses three different problems for the first time in research competition under well-defined conditions: classification of deceptive vs. non-deceptive speech, the estimation of the degree of sincerity, and the identification of the native language out of eleven L1 classes of English L2 speakers. In this paper, we describe these sub-challenges, their conditions, the baseline feature extraction and classifiers, and the resulting baselines, as provided to the participants.

Original languageEnglish (US)
Pages (from-to)2001-2005
Number of pages5
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Volume08-12-September-2016
DOIs
StatePublished - 2016

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Keywords

  • Challenge
  • Computational paralinguistics
  • Deception
  • Native language identification
  • Sincerity

ASJC Scopus subject areas

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

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