Abstract
Humans are notoriously poor at detecting deception - most are worse than chance. To address this issue we have developed LieCatcher, a single-player web-based Game With A Purpose (GWAP) that allows players to assess their lie detection skills while providing human judgments of deceptive speech. Players listen to audio recordings drawn from a corpus of deceptive and non-deceptive interview dialogues, and guess if the speaker is lying or telling the truth. They are awarded points for correct guesses and at the end of the game they receive a score summarizing their performance at lie detection. We present the game design and implementation, and describe a crowdsourcing experiment conducted to study perceived deception.
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CITATION STYLE
Levitan, S. I., Tan, X., & Hirschberg, J. (2020). LieCatcher: Game Framework for Collecting Human Judgments of Deceptive Speech. In ICMI 2020 - Proceedings of the 2020 International Conference on Multimodal Interaction (pp. 762–763). Association for Computing Machinery, Inc. https://doi.org/10.1145/3382507.3421166
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