Automatic Generation of Dialogues based on Grammatical Inference and the use of a Knowledge Base

Issue title: Special section: Selected papers of LKE 2019

Guest editors: David Pinto, Vivek Singh and Fernando Perez

Article type: Research Article

Authors: Vázquez, Andrés^{a; *} | Pinto, David^a | Pallares, Juan^b | De la Rosa, Rafael^b | Tecotl, Elia^b

Affiliations: [a] Language & Knowledge Engineering Lab, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico | [b] Faculty of Computer Science, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico

Correspondence: [*] Corresponding author. Andrés Vázquez, Language & Knowledge Engineering Lab, Benemérita Universidad Autónoma de Puebla, Puebla, Mexico. E-mail: [email protected].

Abstract: In this work, we present a model for the automatic generation of written dialogues, through the use of grammatical inference. This model allows the automatic recognition of grammars from a set dialogues employed as a training set. The inferred grammars are then used to generate templates of responses within the dialogues. The final objective is to apply this model in a specific domain dialogue system that answers questions in Spanish with the use of a knowledge base. The experiments carried out have been performend using the DIHANA project corpus which contains dialogues written in Spanish about schedules and prices of a rail system.

Keywords: Grammatical inference, dialogue system, knowledge base

DOI: 10.3233/JIFS-179876

Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 2105-2113, 2020