Improving social relationships in face-to-face human-agent interactions: when the agent wants to know user’s likes and dislikes - CNRS - Centre national de la recherche scientifique Accéder directement au contenu
Communication Dans Un Congrès Année : 2015

Improving social relationships in face-to-face human-agent interactions: when the agent wants to know user’s likes and dislikes

Résumé

This paper tackles the issue of the detection of users verbal expressions of likes and dislikes in a human-agent interaction. We present a system grounded on the theoretical framework provided by (Martin and White, 2005) that integrates the interaction context by jointly processing agents and users utterances. It is designed as a rule-based and bottom-up process based on a symbolic representation of the structure of the sentence. This article also describes the annotation campaign carried out through Amazon Mechanical Turk for the creation of the evaluation dataset. Finally, we present all measures for rating agreement between our system and the human reference and obtain agreement scores that are equal or higher than substantial agreements.

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Dates et versions

hal-01259923 , version 1 (21-01-2016)

Identifiants

  • HAL Id : hal-01259923 , version 1

Citer

Caroline Langlet, Chloé Clavel. Improving social relationships in face-to-face human-agent interactions: when the agent wants to know user’s likes and dislikes. ACL 2015, Jul 2015, Beijing, China. ⟨hal-01259923⟩
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