Introducing Computational Semantics for Natural Language Understanding in Conversational Nutrition Coaches for Healthy Eating
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Benítez-Guijarro, Antonio; Callejas Carrión, Zoraida; Noguera García, Manuel; Benghazi Akhlaki, KawtarEditorial
MDPI
Materia
Natural language processing Nutrition E-health Voice assistant Semantic processing Multimodal interaction
Date
2018-10-18Referencia bibliográfica
Benítez-Guijarro, A. [et al.]. Introducing Computational Semantics for Natural Language Understanding in Conversational Nutrition Coaches for Healthy Eating. Proceedings 2018, 2, 506; doi:10.3390/proceedings2190506.
Sponsorship
This research has been supported by the project DEP2015-70980-R of the Spanish Ministry of Economy and Competitiveness (MINECO) and European Regional Development Fund (ERDF), as well as, received inputs from the COST Action IC1303 AAPELE.Abstract
Nutrition e-coaches have demonstrated to be a successful tool to foster healthy eating
habits, most of these systems are based on graphical user interfaces where users select the meals
they have ingested from predefined lists and receive feedback on their diet. On one side the use of
conversational interfaces based on natural language processing allows users to interact with the
coach more easily and with fewer restrictions. However, on the other side natural language
introduces more ambiguity, as instead of selecting the input from a predefined finite list of meals,
the user can describe the ingests in many different ways that must be translated by the system into
a tractable semantic representation from which to derive the nutritional aspects of interest. In this
paper, we present a method that improves state-of-the-art approaches by means of the inclusion of
nutritional semantic aspects at different stages during the natural language understanding
processing of the user written or spoken input. The outcome generated is a rich nutritional
interpretation of each user ingest that is independent of the modality used to interact with the
coach.