Cargando…
Neural response generation for task completion using conversational knowledge graph
Effective dialogue generation for task completion is challenging to build. The task requires the response generation system to generate the responses consistent with intent and slot values, have diversity in response and be able to handle multiple domains. The response also needs to be context relev...
Autores principales: | Ahmad, Zishan, Ekbal, Asif, Sengupta, Shubhashis, Bhattacharyya, Pushpak |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9910720/ https://www.ncbi.nlm.nih.gov/pubmed/36758020 http://dx.doi.org/10.1371/journal.pone.0269856 |
Ejemplares similares
-
A dynamic goal adapted task oriented dialogue agent
por: Tiwari, Abhisek, et al.
Publicado: (2021) -
Knowledge grounded medical dialogue generation using augmented graphs
por: Varshney, Deeksha, et al.
Publicado: (2023) -
EmoKbGAN: Emotion controlled response generation using Generative Adversarial Network for knowledge grounded conversation
por: Varshney, Deeksha, et al.
Publicado: (2023) -
Deep cascaded multitask framework for detection of temporal orientation, sentiment and emotion from suicide notes
por: Ghosh, Soumitra, et al.
Publicado: (2022) -
Resolution of grammatical tense into actual time, and its application in Time Perspective study in the tweet space
por: Kamila, Sabyasachi, et al.
Publicado: (2019)