EmoKbGAN: Emotion controlled response generation using Generative Adversarial Network for knowledge grounded conversation

Neural open-domain dialogue systems often fail to engage humans in long-term interactions on popular topics such as sports, politics, fashion, and entertainment. However, to have more socially engaging conversations, we need to formulate strategies that consider emotion, relevant-facts, and user beh...

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Veröffentlicht in:	PloS one 2023-02, Vol.18 (2), p.e0280458-e0280458
Hauptverfasser:	Varshney, Deeksha, Ekbal, Asif, Tiwari, Mrigank, Nagaraja, Ganesh Prasad
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence Biology and Life Sciences Cognition & reasoning Communication Computer and Information Sciences Datasets Discriminators Emotions Generative adversarial networks Humans Image Processing, Computer-Assisted - methods Interactive computer systems Knowledge Maximum likelihood estimation Neural networks Neural Networks, Computer Sentences Social Sciences
Online-Zugang:	Volltext
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