NDLI: A Multimodal Corpus Approach to the Design of Virtual Recruiters

Content Provider	IEEE Xplore Digital Library
Author	Chollet, M. Ochs, M. Clavel, C. Pelachaud, C.
Copyright Year	2013
Description	Author affiliation: Inst. Mines-Telecom, Telecom ParisTech, Paris, France (Chollet, M.; Ochs, M.; Clavel, C.; Pelachaud, C.)
Abstract	This paper presents the analysis of the multimodal behavior of experienced practitioners of job interview coaching, and describes a methodology to specify their behavior in Embodied Conversational Agents acting as virtual recruiters displaying different interpersonal stances. In a first stage, we collect a corpus of videos of job interview enactments, and we detail the coding scheme used to encode multimodal behaviors and contextual information. From the annotations of the practitioners' behaviors we observe specificities of behavior across different levels, namely monomodal behavior variations, inter-modalities behavior influences, and contextual influences on behavior. Finally we propose the adaptation of an existing agent architecture to model these specificities in a virtual recruiter's behavior.
Starting Page	19
Ending Page	24
File Size	480751
Page Count	6
File Format	PDF
ISBN	9780769550480
ISSN	21568111
DOI	10.1109/ACII.2013.10
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-09-02
Publisher Place	Switzerland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Context Adaptation models Multimodal corpora Hidden Markov models Encoding Interviews Eyebrows Nonverbal behavior Videos Embodied conversational agents
Content Type	Text
Resource Type	Article

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