Is deception emotional? An emotion-driven predictive approach

Shahin Amiriparian; Jouni Pohjalainen; Erik Marchi; Sergey Pugachevskiy; Björn Schuller

doi:10.21437/Interspeech.2016-565

Is deception emotional? An emotion-driven predictive approach

Shahin Amiriparian
, Jouni Pohjalainen
, Erik Marchi
, Sergey Pugachevskiy
, Björn Schuller

Universität Passau
Technical University of Munich
Imperial College London

Research output: Contribution to journal › Conference article › peer-review

21 Scopus citations

Abstract

In this paper, we propose a method for automatically detecting deceptive speech by relying on predicted scores derived from emotion dimensions such as arousal, valence, regulation, and emotion categories. The scores are derived from task-dependent models trained on the GEMEP emotional speech database. Inputs from the INTERSPEECH 2016 Computational Paralinguistics Deception sub-challenge are processed to obtain predictions of emotion attributes and associated scores that are then used as features in detecting deception. We show that using the new emotion-related features, it is possible to improve upon the challenge baseline.

Original language	English
Pages (from-to)	2011-2015
Number of pages	5
Journal	Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Volume	08-12-September-2016
DOIs	https://doi.org/10.21437/Interspeech.2016-565
State	Published - 2016
Externally published	Yes
Event	17th Annual Conference of the International Speech Communication Association, INTERSPEECH 2016 - San Francisco, United States Duration: 8 Sep 2016 → 16 Sep 2016

Keywords

Computational paralinguistics
Deception
Emotion

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10.21437/Interspeech.2016-565

Cite this

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title = "Is deception emotional? An emotion-driven predictive approach",

abstract = "In this paper, we propose a method for automatically detecting deceptive speech by relying on predicted scores derived from emotion dimensions such as arousal, valence, regulation, and emotion categories. The scores are derived from task-dependent models trained on the GEMEP emotional speech database. Inputs from the INTERSPEECH 2016 Computational Paralinguistics Deception sub-challenge are processed to obtain predictions of emotion attributes and associated scores that are then used as features in detecting deception. We show that using the new emotion-related features, it is possible to improve upon the challenge baseline.",

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volume = "08-12-September-2016",

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T1 - Is deception emotional? An emotion-driven predictive approach

AU - Amiriparian, Shahin

AU - Pohjalainen, Jouni

AU - Marchi, Erik

AU - Pugachevskiy, Sergey

AU - Schuller, Björn

PY - 2016

Y1 - 2016

N2 - In this paper, we propose a method for automatically detecting deceptive speech by relying on predicted scores derived from emotion dimensions such as arousal, valence, regulation, and emotion categories. The scores are derived from task-dependent models trained on the GEMEP emotional speech database. Inputs from the INTERSPEECH 2016 Computational Paralinguistics Deception sub-challenge are processed to obtain predictions of emotion attributes and associated scores that are then used as features in detecting deception. We show that using the new emotion-related features, it is possible to improve upon the challenge baseline.

AB - In this paper, we propose a method for automatically detecting deceptive speech by relying on predicted scores derived from emotion dimensions such as arousal, valence, regulation, and emotion categories. The scores are derived from task-dependent models trained on the GEMEP emotional speech database. Inputs from the INTERSPEECH 2016 Computational Paralinguistics Deception sub-challenge are processed to obtain predictions of emotion attributes and associated scores that are then used as features in detecting deception. We show that using the new emotion-related features, it is possible to improve upon the challenge baseline.

KW - Computational paralinguistics

KW - Deception

KW - Emotion

UR - https://www.scopus.com/pages/publications/84994338824

U2 - 10.21437/Interspeech.2016-565

DO - 10.21437/Interspeech.2016-565

M3 - Conference article

AN - SCOPUS:84994338824

SN - 2308-457X

VL - 08-12-September-2016

SP - 2011

EP - 2015

JO - Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

JF - Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

T2 - 17th Annual Conference of the International Speech Communication Association, INTERSPEECH 2016

Y2 - 8 September 2016 through 16 September 2016

ER -

Is deception emotional? An emotion-driven predictive approach

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Keywords

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