[1]

FITZPATRICK E, BACHENKO J, FORNACIARI T. Automatic Detection of Verbal Deception[M]. USA: Morgan & Claypool Publisher, 2015.

[2]

PENNEBAKER J W, FRANCIS M E, BOOTH R J. Lin-guis tic inquiry and word count: LIWC 2001[EB/OL]. scholar. google. cn, 2001-03-28 [2019-09-04]. http://www.depts.ttu.edu/psy/lusi/files/LIWCmanual.pdf.

[3] NEWMAN M L, PENNEBAKER J W, BERRY D S, et al.  Lying words: Predicting deception from linguistic styles[J]. Personality and Social Psychology Bulletin, 2003, 29(5): 665-675.   doi: 10.1177/0146167203029005010
[4] ZHOU L, BURGOON J K, NUNAMAKER J F, et al.  Automating linguistics-based cues for detecting deception in text-based asynchronous computer-mediated communications[J]. Group Decision and Negotiation, 2004, 13(1): 81-106.   doi: 10.1023/B:GRUP.0000011944.62889.6f
[5]

MIHALCEA R, PULMAN S. Linguistic ethnography: Identifying dominant word classes in text[C]//International Conference on Intelligent Text Processing and Computational Linguistics. Berlin, Heidelberg: Springer, 2009: 594-602.

[6]

YANCHEVA M, RUDZICZ F. Automatic detection of deception in child-produced speech using syntactic complexity features[C]//Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics. Bulgaria: Association for Computational Linguistics, 2013: 944-953.

[7]

PÉREZ-ROSAS V, ABOUELENIEN M, MIHALCEA R, et al. Deception detection using real-life trial data[C]//Proceedings of the 2015 ACM on International Conference on Multimodal Interaction. USA: ACM, 2015: 59-66.

[8]

ABRAMS S. The Complete Polygraph Handbook[M]. England: Lexington Books/DC Heath and Com, 1989.

[9]

ABOUELENIEN M, PÉREZ-ROSAS V, MIHALCEA R, et al. Deception detection using a multimodal approach[C]//Proceedings of the 16th International Conference on Multimodal Interaction. USA: ACM, 2014: 58-65.

[10] PAVLIDIS I, EBERHARDT N L, LEVINE J A.  Human behaviour: Seeing through the face of deception[J]. Nature, 2002, 415(6867): 35-.
[11] POLLINA D A, DOLLINS A B, SENTER S M, et al.  Facial skin surface temperature changes during a “concealed information” test[J]. Annals of Biomedical Engineering, 2006, 34(7): 1182-1189.   doi: 10.1007/s10439-006-9143-3
[12] SIMPSON J R.  Functional MRI lie detection: Too good to be true?[J]. The Journal of the American Academy of Psychiatry and the Law, 2008, 36(4): 491-498.
[13] APPLE W, STREETER L A, KRAUSS R M.  Effects of pitch and speech rate on personal attributions[J]. Journal of Personality and Social Psychology, 1979, 37(5): 715-727.   doi: 10.1037/0022-3514.37.5.715
[14]

GRACIARENA M, SHRIBERG E, STOLCKE A, et al. Combining prosodic lexical and cepstral systems for deceptive speech detection[C]//2006 IEEE International Conference on Acoustics Speech and Signal Processing. France: IEEE, 2006: 1033-1036.

[15]

BENUS S, ENOS F, HIRSCHBERG J, et al. Pauses in deceptive speech[EB/OL]. scholar. google. cn, 2013-06-28 [2019-09-04]. https://academiccommons.columbia.edu/doi/10.7916/D8SQ97TG.

[16]

KIRCHHUEBEL C. The acoustic and temporal characteristics of deceptive speech[D]. UK: University of York, 2013.

[17] DEPAULO B M, LINDSAY J J, MALONE B E, et al.  Cues to deception[J]. Psychological Bulletin, 2003, 129(1): 74-118.   doi: 10.1037/0033-2909.129.1.74-118
[18]

EKMAN P. Telling Lies: Clues to Deceit in the Marketplace, Politics, and Marriage[M]. USA: WW Norton & Company, 2009.

[19]

WU Z, SINGH B, DAVIS L S, et al. Deception detection in videos[EB/OL]. scholar. google. cn, 2018-04-25 [2019-09-04]. https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/viewPaper/16926.

[20] CASO L, MARICCHIOLO F, BONAIUTO M, et al.  The impact of deception and suspicion on different hand movements[J]. Journal of Nonverbal Behavior, 2006, 30(1): 1-19.   doi: 10.1007/s10919-005-0001-z
[21] COHEN D, BEATTIE G, SHOVELTON H.  Nonverbal indicators of deception: How iconic gestures reveal thoughts that cannot be suppressed[J]. Semiotica, 2010, 182: 133-174.
[22]

LEVITAN S I, AN G, MA M, et al. Combining acoustic-prosodic, lexical, and phonotactic features for automatic deception detection [EB/OL]. scholar. google. cn, 2016-09-08 [2019-09-04]. http://dx.doi.org/10.21437/Interspeech.2016-1519.

[23]

KRISHNAMURTHY G, MAJUMDER N, PORIA S, et al. A deep learning approach for multimodal deception detection[EB/OL].arxiv.org, 2018-03-01[2019-06-10]. https://arxiv.org/abs/1803.00344.

[24]

KARIMI H, TANG J, LI Y. Toward end-to-end deception detection in videos[C]//2018 IEEE International Conference on Big Data (Big Data). USA: IEEE, 2018: 1278-1283.

[25] POH M Z, MCDUFF D J, PICARD R W.  Non-contact, automated cardiac pulse measurements using video imaging and blind source separation[J]. Optics Express, 2010, 18(10): 10762-10774.   doi: 10.1364/OE.18.010762
[26] VERKRUYSSE W, SVAASAND L O, NELSON J S.  Remote plethysmographic imaging using ambient light[J]. Optics Express, 2008, 16(26): 21434-21445.   doi: 10.1364/OE.16.021434
[27]

ABOUELENIEN M, MIHALCEA R, BURZO M. Analyzing thermal and visual clues of deception for a non-contact deception detection approach[C]//Proceedings of the 9th ACM International Conference on PErvasive Technologies Related to Assistive Environments. Greece: ACM, 2016: 1-4.

[28] JI S, XU W, YANG M, et al.  3D convolutional neural networks for human action recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(1): 221-231.   doi: 10.1109/TPAMI.2012.59