research-article

Multilingual Deception Detection by Autonomous Agents

Authors:

Evgeny Hershkovitch Neiterman,

Moshe Bitan,

Amos AzariaAuthors Info & Claims

WWW '20: Companion Proceedings of the Web Conference 2020

Pages 480 - 484

https://doi.org/10.1145/3366424.3384369

Published: 20 April 2020 Publication History

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Abstract

In this work we present the development of a multilingual deception detection model based on speech. In addition, we also develop a model that detects whether a statement will be perceived as a lie or not by human subjects. To this end, we developed a game for collecting a large scale and high quality labeled data-set in a controlled environments in English and Hebrew. We developed a model that can detect deception based only on a vocal statement from the participants of the experiment. The data-set will be released to the community.

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Cited By

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King SNeal T(2024)Applications of AI-Enabled Deception Detection Using Video, Audio, and Physiological Data: A Systematic ReviewIEEE Access10.1109/ACCESS.2024.346282512(135207-135240)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3462825
Constâncio ATsunoda DSilva HSilveira JCarvalho D(2023)Deception detection with machine learning: A systematic review and statistical analysisPLOS ONE10.1371/journal.pone.028132318:2(e0281323)Online publication date: 9-Feb-2023
https://doi.org/10.1371/journal.pone.0281323
Jiang YChen HYuan SXing HCao YWang DXiong H(2023)Speech Deception Detection Based on EMD and Temporal Neural NetworkComputational Intelligence and Neuroscience10.1155/2023/66708692023(1-9)Online publication date: 29-May-2023
https://doi.org/10.1155/2023/6670869
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Index Terms

Multilingual Deception Detection by Autonomous Agents
1. Applied computing
2. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Intelligent agents
      2. Multi-agent systems
    2. Natural language processing

Index terms have been assigned to the content through auto-classification.

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Published In

WWW '20: Companion Proceedings of the Web Conference 2020

April 2020

854 pages

ISBN:9781450370240

DOI:10.1145/3366424

Editors:
Amal El Fallah Seghrouchni
Sorbonne University, France
,
Gita Sukthankar
University of Central Florida, United States
,
Tie-Yan Liu
Microsoft Research Asia, China
,
Maarten van Steen
University of Twente, Netherlands

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 20 April 2020

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WWW '20: The Web Conference 2020

April 20 - 24, 2020

Taipei, Taiwan

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King SNeal T(2024)Applications of AI-Enabled Deception Detection Using Video, Audio, and Physiological Data: A Systematic ReviewIEEE Access10.1109/ACCESS.2024.346282512(135207-135240)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3462825
Constâncio ATsunoda DSilva HSilveira JCarvalho D(2023)Deception detection with machine learning: A systematic review and statistical analysisPLOS ONE10.1371/journal.pone.028132318:2(e0281323)Online publication date: 9-Feb-2023
https://doi.org/10.1371/journal.pone.0281323
Jiang YChen HYuan SXing HCao YWang DXiong H(2023)Speech Deception Detection Based on EMD and Temporal Neural NetworkComputational Intelligence and Neuroscience10.1155/2023/66708692023(1-9)Online publication date: 29-May-2023
https://doi.org/10.1155/2023/6670869
Zhang ZWan JZhou MLai ZTessone CChen GLiao H(2023)Temporal burstiness and collaborative camouflage aware fraud detectionInformation Processing & Management10.1016/j.ipm.2022.10317060:2(103170)Online publication date: Mar-2023
https://doi.org/10.1016/j.ipm.2022.103170
Rodriguez-Diaz NAspandi DSukno FBinefa X(2021)Machine Learning-Based Lie Detector Applied to a Novel Annotated Game DatasetFuture Internet10.3390/fi1401000214:1(2)Online publication date: 21-Dec-2021
https://doi.org/10.3390/fi14010002
Cao CLi SYu SChen Z(2021)Fake Reviewer Group Detection in Online Review Systems2021 International Conference on Data Mining Workshops (ICDMW)10.1109/ICDMW53433.2021.00122(935-942)Online publication date: Dec-2021
https://doi.org/10.1109/ICDMW53433.2021.00122

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Abstract

References

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Recommendations

Cross-Cultural Production and Detection of Deception from Speech

Building a corpus of "real" texts for deception detection

On Detecting Deception in Agent Societies

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