Towards sentiment aided dialogue policy learning for multi-intent conversations using hierarchical reinforcement learning

PURPOSE: Developing a Dialogue/Virtual Agent (VA) that can handle complex tasks (need) of the user pertaining to multiple intents of a domain is challenging as it requires the agent to simultaneously deal with multiple subtasks. However, majority of these end-to-end dialogue systems incorporate only...

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Detalles Bibliográficos
Autores principales: Saha, Tulika, Saha, Sriparna, Bhattacharyya, Pushpak
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7332012/
https://www.ncbi.nlm.nih.gov/pubmed/32614929
http://dx.doi.org/10.1371/journal.pone.0235367

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7332012/
https://www.ncbi.nlm.nih.gov/pubmed/32614929
http://dx.doi.org/10.1371/journal.pone.0235367

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