A proposal for Developing and Deploying Statistical Dialog Management in Commercial Conversational Platforms
Identificadores
URI: https://hdl.handle.net/10481/80260Metadata
Show full item recordEditorial
Springer
Materia
Conversational systems Dialog management Statistical approaches DialogFlow
Date
2022Referencia bibliográfica
This is a pre-print version of the chapter: Cañas, P., Griol, D., Callejas, Z. (2022). A Proposal for Developing and Deploying Statistical Dialog Management in Commercial Conversational Platforms. In: , et al. Hybrid Artificial Intelli- gent Systems. HAIS 2022. Lecture Notes in Computer Science(), vol 13469. Springer, Cham. https://doi.org/10. 1007/978-3-031-15471-3_35 (https://link.springer.com/chapter/10.1007/978-3-031-15471-3_35)
Abstract
Conversational interfaces have recently become ubiquitous in the personal sphere by improving
an individual’s quality of life and industrial environments by automating services and their corre-
sponding cost savings. However, designing the dialog model used by these interfaces to decide
the following response is a hard-to-accomplish task for complex conversational interactions. This
paper proposes a statistical-based dialog manager architecture, which provides flexibility to develop
and maintain this module. Our proposal has been integrated using DialogFlow, a natural language
understanding platform provided by Google to design conversational user interfaces. The proposed
hybrid architecture has been assessed with a real use case for a train scheduling domain, proving that
the user experience is highly valued and can be integrated into commercial setups