A Novel Hybrid Network Model Based on Attentional Multi-Feature Fusion for Deception Detection-Reference-Cited by-同舟云学术

A Novel Hybrid Network Model Based on Attentional Multi-Feature Fusion for Deception Detection

Published:2021-03-01 Issue:3 Volume:E104.A Page:622-626
ISSN:0916-8508
Container-title:IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
language:en
Short-container-title:IEICE Trans. Fundamentals

Author:

FANG Yuanbo¹²,FU Hongliang¹²,TAO Huawei¹²³,LIANG Ruiyu⁴,ZHAO Li³

Affiliation:

1. Key Laboratory of Grain Information Processing and Control, (Henan University of Technology), Ministry of Education

2. College of Information Science and Engineering, Henan University of Technology

3. School of Information Science and Engineering, Southeast University

4. School of Communication Engineering, Nanjing Institute of Technology

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Signal Processing

Link

https://www.jstage.jst.go.jp/article/transfun/E104.A/3/E104.A_2020EAL2051/_pdf

Reference13 articles.

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3. [3] Y. Xie, R. Liang, Y. Bao, et al., “Deception detection with spectral features based on deep belief network,” ACTA ACUSTICA, vol.2, pp.214-210, 2019.

4. [4] H. Fu, P. Lei, H. Tao, L. Zhao, J. Yang, and J. Zhang, “Improved semi-supervised autoencoder for deception detection,” PLOS ONE, vol.14, no.10, 2019. 10.1371/journal.pone.0223361

5. [5] B.-H. Su, S.-L. Yeh, M.-Y. Ko, H.-Y. Chen, S.-C. Zhong, J.-L. Li, and C.-C. Lee, “Self-assessed affect recognition using fusion of attentional BLSTM and static acoustic features,” Interspeech, pp.536-540, 2018. 10.21437/interspeech.2018-2261

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