Abstract
A serious game for learning the social skills required for effective police interviewing is a challenging idea. Building artificial conversational characters that play the role of a suspect in a police interrogation game requires computational models of police interviews as well as of the internal psychological mechanisms that determine the behaviour of suspects in this special type of dialogues. Leary{\textquoteright}s interactional circumplex is used in police interview training as a theoretical framework to understand how suspects take stance during an interview and how this is related to the stance and the strategy that the interviewer takes. Interactional stance is a fuzzy notion. The question that we consider here is whether different observers of police interviews agree on the type of stance that suspect and policemen take and express in a face-to-face interview. We analyzed police interviews and report about a stance annotation exercise. We conclude that although inter- annotator agreement on stance labeling on the level of speech segments is low, a majority voting {\textquotedblleft}meta-annotator{\textquotedblright} is able to reveal the important dynamics in stance taking in a police interview. Then we explore the relation between the stance taken by the suspect and turn-taking behaviour, overlaps, interruptions, pauses and silences. Our findings contribute to building computational models of non-player characters that allow more natural turn-taking behaviour in serious games instead of the one-at-a-time regime in interview training games.
Original language | English |
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Pages (from-to) | 193-216 |
Number of pages | 24 |
Journal | Computational linguistics in the Netherlands journal |
Volume | 3 |
Publication status | Published - 20 Dec 2013 |
Keywords
- Content analyis
- Police Interview
- Interpersonal stance
- Turn taking
- HMI-HF: Human Factors