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emotional dialog generation via multiple classifiers based on a generative adversarial network

Virtual Reality & Intelligent Hardware 2021年第1期3卷 18-32页

作者： Wei CHEN Xinmiao CHEN Xiao SUN School of Computer and Information Hefei University of TechnologyHefei 230601China

Background Human-machine dialog generation is an essential topic of research in the field of natural language *** high-quality,diverse,fluent,and emotional conversation is a challenging *** on continuing advancements in artificial intelligence and deep learning,new methods have come to the forefront in recent *** particular,the end-to-end neural network model provides an extensible conversation generation framework that has the potential to enable machines to understand semantics and automatically generate ***,neural network models come with their own set of questions and *** basic conversational model framework tends to produce universal,meaningless,and relatively"safe"*** Based on generative adversarial networks(GANs),a new emotional dialog generation framework called EMC-GAN is proposed in this study to address the task of emotional dialog *** proposed model comprises a generative and three discriminative *** generator is based on the basic sequence-to-sequence(Seq2Seq)dialog generation model,and the aggregate discriminative model for the overall framework consists of a basic discriminative model,an emotion discriminative model,and a fluency discriminative *** basic discriminative model distinguishes generated fake sentences from real sentences in the training *** emotion discriminative model evaluates whether the emotion conveyed via the generated dialog agrees with a pre-specified emotion,and directs the generative model to generate dialogs that correspond to the category of the pre-specified ***,the fluency discriminative model assigns a score to the fluency of the generated dialog and guides the generator to produce more fluent *** Based on the experimental results,this study confirms the superiority of the proposed model over similar existing models with respect to emotional accuracy,fluency,and *** The proposed EMC-

关键词： emotional dialog generation Sequence-to-sequence model Emotion classification Generative adversarial networks Multiple classifiers

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