Deception detecting from speech signal using relevance vector machine and non-linear dynamics features-Reference-Cited by-同舟云学术

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Deception detecting from speech signal using relevance vector machine and non-linear dynamics features

Published:2015-03 Issue: Volume:151 Page:1042-1052
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Zhou Yan,Zhao Heming,Pan Xinyu,Shang Li

Funder

National Natural Science Foundations of China

National Natural Science Foundation of China

Innovative team foundation of Suzhou vocational university and the Innovative Plan Project for Graduate students of Jiangsu province

Natural Science Foundation of Jiangsu Province

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference37 articles.

1. Accuracy of deception judgments;Bond;Personal. Soc. Psychol. Rev.,2006

2. Sequence-based prediction of protein-protein interactions by means of rotation forest and autocorrelation descriptor;Xia;Protein and Peptide Letters,2010

3. Tumor clustering using non-negative matrix factorization with gene selection;Zheng;IEEE Trans. Inf. Technol. Biomed.,2009

4. Indicators of veracity and deception: an analysis of written statements made to police;Adams;Int. J. Speech, Lang. Law,2006

5. Who can best catch a liar?;Aamodt;Forensic Examiner,2006

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1. EEG-based deception detection using weighted dual perspective visibility graph analysis;Cognitive Neurodynamics;2024-09-13

2. A semi-supervised high-quality pseudo labels algorithm based on multi-constraint optimization for speech deception detection;Computer Speech & Language;2024-04

3. Deception detection using machine learning (ML) and deep learning (DL) techniques: A systematic review;Natural Language Processing Journal;2024-03

4. An Overview of Advancements in Lie Detection Technology in Speech;International Journal of Information Technologies and Systems Approach;2023-01-20

5. Therapist Perceptions of Automated Deception Detection in Mental Health Applications;Artificial Intelligence in HCI;2023

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