An Adversarial Learning Framework For A Persona-Based Multi-Turn Dialogue Model

@article{Olabiyi2019AnAL,
  title={An Adversarial Learning Framework For A Persona-Based Multi-Turn Dialogue Model},
  author={O. Olabiyi and Anish Khazane and A. Salimov and Erik T. Mueller},
  journal={ArXiv},
  year={2019},
  volume={abs/1905.01992}
}
In this paper, we extend the persona-based sequence-to-sequence (Seq2Seq) neural network conversation model to a multi-turn dialogue scenario by modifying the state-of-the-art hredGAN architecture to simultaneously capture utterance attributes such as speaker identity, dialogue topic, speaker sentiments and so on. [...] Key Method We also explore two approaches to accomplish the conditional discriminator: (1) phredGAN_a, a system that passes the attribute representation as an additional input into a traditional…Expand
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