Abstract

Constructing computational models of interactions during Forensic Interviews (FI) with children presents a unique challenge in being able to maximize complete and accurate information disclosure, while minimizing emotional trauma experienced by the child. Leveraging multiple channels of observational signals, dynamical system modeling is employed to track and identify patterns in the influence interviewers' linguistic and paralinguistic behavior has on children's verbal recall productivity. Specifically, linear mixed effects modeling and dynamical mode decomposition allow for robust analysis of acoustic-prosodic features, aligned with lexical features at turn-level utterances. By varying the window length, the model parameters evaluate both interviewer and child behaviors at different temporal resolutions, thus capturing both rapport-building and disclosure phases of FI. Making use of a recently proposed definition …

Date

2018

Authors

Victor Ardulov, Madelyn Mendlen, Manoj Kumar, Neha Anand, Shanna Williams, Thomas Lyon, Shrikanth Narayanan

Book

Proceedings of the 20th ACM International Conference on Multimodal Interaction

Pages

179-185