Managing Multi-task Dialogs by Means of a Statistical Dialog Management Technique

Griol Barres, David; Callejas Carrión, Zoraida; Quesada, José F.

21_GriolCallejasQuesada_Preprint.pdf (208.3Kb)

Identificadores

URI: https://hdl.handle.net/10481/80254

Exportar

Editorial

Springer

Materia

Dialogue management

Multi-task dialogue

Fecha

2021

Referencia bibliográfica

Published version: Griol, D., Callejas, Z., Quesada, J.F. (2021). Managing Multi-task Dialogs by Means of a Statistical Dialog Management Technique. In: Marchi, E., Siniscalchi, S.M., Cumani, S., Salerno, V.M., Li, H. (eds) Increasing Naturalness and Flexibility in Spoken Dialogue Interaction. Lecture Notes in Electrical Engineering, vol 714. Springer, Singapore. [https://doi.org/10.1007/978-981-15-9323-9_6]

Patrocinador

info:eu-repo/grantAgreement/EC/H2020/823907 CAVIAR project (MINECO, TEC2017-84593-C2-1-R, AEI/FEDER, UE)

Resumen

One of the most demanding tasks when developing a dialog system consists of deciding the next system response considering the user’s actions and the dialog history, which is the fundamental responsibility related to dialog management. A statistical dialog management technique is proposed in this work to reduce the effort and time required to design the dialog manager. This technique allows not only an easy adaptation to new domains, but also to deal with the different subtasks for which the dialog system has been designed. The practical application of the proposed technique to develop a dialog system for a travel-planning domain shows that the use of task-specific dialog models increases the quality and number of successful interactions with the system in comparison with developing a single dialog model for the complete domain.