The recognition of acted interpersonal stance in police interrogations and the influence of actor proficiency

This paper reports on judgement studies regarding the perception of interpersonal stances taken by humans playing the role of a suspect in a police interrogation setting. Our project aims at building believable embodied conversational characters to play the role of suspects in a serious game for learning interrogation strategies. The main question we ask is: do human judges agree on the way they perceive the various aspects of stance taking, such as friendliness and dominance? Four types of stances were acted by eight amateur actors. Short recordings were shown in an online survey to subjects who were asked to describe them using a selection of a number of adjectives. Results of this annotation task are reported in this paper. We explain how we computed the inter-rater agreement with Krippendorff’s alpha statistics using a set theoretical distance metric. Results show that for some of the stance types observers agreed more than for others. Some actors are better than others, but validity (recognizing the intended stance) and inter-rater agreement do not always go hand in hand. We further investigate the effect the expertise of actors has on the perception of the stance that is acted. We compare the fragments from amateur actors to fragments from professional actors taken from popular TV-shows.

[1]  Pär Anders Granhag,et al.  The Detection of Deception in Forensic Contexts , 2005 .

[2]  Emiel Krahmer,et al.  Real vs. acted emotional speech , 2006, INTERSPEECH.

[3]  Maja Pantic,et al.  Social signal processing: Survey of an emerging domain , 2009, Image Vis. Comput..

[4]  Merijn Bruijnes,et al.  Interpersonal stance in police interviews: content analysis , 2013, CLIN 2013.

[5]  Rieks op den Akker,et al.  The recognition of acted interpersonal stance in police interrogations , 2013 .

[6]  K. Scherer What are emotions? And how can they be measured? , 2005 .

[7]  Walter Daelemans,et al.  Automatic Emotion Classification for Interpersonal Communication , 2011, WASSA@ACL.

[8]  Walter Daelemans,et al.  Emotion Classification in a Serious Game for Training Communication Skills , 2010 .

[9]  Maria Hartwig,et al.  The Detection of Deception in Forensic Contexts: Practitioners' beliefs about deception , 2004 .

[10]  D. Ballin,et al.  A framework for interpersonal attitude and non-verbal communication in improvisational visual media production , 2004 .

[11]  Michael Neff,et al.  Evaluating the Effect of Gesture and Language on Personality Perception in Conversational Agents , 2010, IVA.

[12]  Dale E. Olsen Interview and Interrogation Training using a Computer-Simulated Subject , 1997 .

[13]  Nicole Novielli,et al.  Modeling User Interpersonal Stances in Affective Dialogues with an ECA , 2009, International Conference on Software Engineering and Knowledge Engineering.

[14]  Catherine Pelachaud,et al.  Mining a multimodal corpus for non-verbal behavior sequences conveying attitudes , 2014, LREC.

[15]  J. Burgoon,et al.  Nonverbal Communication , 2018, Encyclopedia of Evolutionary Psychological Science.

[16]  Catherine Pelachaud,et al.  Interpersonal stance recognition using non-verbal signals on several time windows , 2012 .

[17]  David Luciew,et al.  Finding the Truth: Interview and Interrogation Training Simulations , 2011 .

[18]  Shrikanth S. Narayanan,et al.  Recording audio-visual emotional databases from actors : a closer look , 2008 .

[19]  K. Scherer,et al.  The Body Action and Posture Coding System (BAP): Development and Reliability , 2012 .

[20]  Judith A. Hall,et al.  Beliefs about the nonverbal expression of social power , 2005 .

[21]  Jan van Dalen,et al.  Leary's Rose to improve negotiation skills among health professionals: experiences from a Southeast Asian culture. , 2013, Education for health.

[22]  Ellen Giebels,et al.  Are you talking to me? Influencing behaviour and culture in police interviews , 2009 .

[23]  Klaus R. Scherer,et al.  Using Actor Portrayals to Systematically Study Multimodal Emotion Expression: The GEMEP Corpus , 2007, ACII.

[24]  Walter Daelemans,et al.  deLearyous : an interactive application for interpersonal communication training , 2011 .

[25]  R. Birdwhistell Kinesics and context , 1970 .

[26]  Marco Gillies,et al.  A Model of Interpersonal Attitude and Posture Generation , 2003, IVA.

[27]  Robert Gifford,et al.  A lens-mapping framework for understanding the encoding and decoding of interpersonal dispositions in nonverbal behavior. , 1994 .

[28]  Fred E. Inbau,et al.  Essentials of the Reid Technique: Criminal Interrogation and Confessions , 2013 .

[29]  Klaus Krippendorff,et al.  Content Analysis: An Introduction to Its Methodology , 1980 .

[30]  P. Baranyi,et al.  Definition and synergies of cognitive infocommunications , 2012 .

[31]  Fred E. Inbau,et al.  Criminal Interrogation and Confessions , 1967 .

[32]  Andrea Kleinsmith,et al.  Affective Body Expression Perception and Recognition: A Survey , 2013, IEEE Transactions on Affective Computing.

[33]  K. Scherer,et al.  Introducing the Geneva Multimodal expression corpus for experimental research on emotion perception. , 2012, Emotion.

[34]  David Traum Non-cooperative and Deceptive Virtual Agents , 2012 .

[35]  Ron Artstein,et al.  Survey Article: Inter-Coder Agreement for Computational Linguistics , 2008, CL.

[36]  Tamás D. Gedeon,et al.  Emotion Recognition In The Wild Challenge 2014: Baseline, Data and Protocol , 2014, ICMI.

[37]  Ursula Hess,et al.  Why the Same Expression May Not Mean the Same When Shown on Different Faces or Seen by Different People , 2009, Affective Information Processing.

[38]  Aaron L. Pincus,et al.  Paradigms of Personality Assessment , 2003 .

[39]  Elisabeth André,et al.  Integration of cultural factors into the behavioral models of virtual characters , 2014, Natural Language Generation in Interactive Systems.

[40]  Timothy Leary,et al.  Interpersonal diagnosis of personality : a functional theory and methodology for personality evaluation , 1958 .

[41]  K. Scherer,et al.  Emotion expression in body action and posture. , 2012, Emotion.

[42]  Danny Rouckhout,et al.  Ontwikkeling van een Nederlandstalig interpersoonlijk circumplex , 2000 .

[43]  M. Lévesque Perception , 1986, The Yale Journal of Biology and Medicine.

[44]  Stacy Marsella,et al.  Building Interactive Virtual Humans for Training Environments , 2007 .

[45]  P. Ekman,et al.  Facial action coding system: a technique for the measurement of facial movement , 1978 .

[46]  Sandra S. Smith-Hanen Effects of Nonverbal Behaviors on Judged Levels of Counselor Warmth and Empathy. , 1977 .

[47]  M. Argyle Bodily communication, 2nd ed. , 1988 .

[48]  Harald C. Traue,et al.  The effect of forced choice on facial emotion recognition: a comparison to open verbal classification of emotion labels , 2013, Psycho-social medicine.

[49]  Srinivas Bangalore,et al.  Natural Language Generation in Interactive Systems , 2014 .

[50]  L. R. Dice Measures of the Amount of Ecologic Association Between Species , 1945 .

[51]  P. Ekman,et al.  What the face reveals : basic and applied studies of spontaneous expression using the facial action coding system (FACS) , 2005 .

[52]  J. S. Wiggins,et al.  Psychometric and Geometric Characteristics of the Revised Interpersonal Adjective Scales (IAS-R). , 1988, Multivariate behavioral research.

[53]  Abdullah Zawawi Talib,et al.  An Intelligent Instructional Tool for Puppeteering in Virtual Shadow Puppet Play , 2011, INTETAIN.

[54]  Dirk Heylen,et al.  First Impressions: Users' Judgments of Virtual Agents' Personality and Interpersonal Attitude in First Encounters , 2012, IVA.

[55]  Dirk Heylen,et al.  The Sensitive Artificial Listner: an induction technique for generating emotionally coloured conversation , 2008 .

[56]  Brian Ravenet A computational model of social attitude effects on the nonverbal behavior for a relational agent , 2012 .