Cargando…
Diversifying Emotional Dialogue Generation via Selective Adversarial Training
Emotional perception and expression are very important for building intelligent conversational systems that are human-like and attractive. Although deep neural approaches have made great progress in the field of conversation generation, there is still a lot of room for research on how to guide syste...
Autores principales: | Li, Bo, Zhao, Huan, Zhang, Zixing |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10346147/ https://www.ncbi.nlm.nih.gov/pubmed/37447753 http://dx.doi.org/10.3390/s23135904 |
Ejemplares similares
-
Generative Adversarial Training for Supervised and Semi-supervised Learning
por: Wang, Xianmin, et al.
Publicado: (2022) -
Emotion dynamics in movie dialogues
por: Hipson, Will E., et al.
Publicado: (2021) -
Emotion Recognition Based on EEG Using Generative Adversarial Nets and Convolutional Neural Network
por: Pan, Bo, et al.
Publicado: (2021) -
Machine learning through cryptographic glasses: combating adversarial attacks by key-based diversified aggregation
por: Taran, Olga, et al.
Publicado: (2020) -
Distributed Training of Generative Adversarial Networks for Fast Simulation
por: Vallecorsa, Sofia, et al.
Publicado: (2019)