  Child Forensic Interviewing (FI) presents a challenge for effective
information retrieval and decision making. The high stakes associated with the
process demand that expert legal interviewers are able to effectively establish
a channel of communication and elicit substantive knowledge from the
child-client while minimizing potential for experiencing trauma. As a first
step toward computationally modeling and producing quality spoken interviewing
strategies and a generalized understanding of interview dynamics, we propose a
novel methodology to computationally model effectiveness criteria, by applying
summarization and topic modeling techniques to objectively measure and rank the
responsiveness and conversational productivity of a child during FI. We score
information retrieval by constructing an agenda to represent general topics of
interest and measuring alignment with a given response and leveraging lexical
entrainment for responsiveness. For comparison, we present our methods along
with traditional metrics of evaluation and discuss the use of prior information
for generating situational awareness.
