End to End Dialogue Transformer

Ondřej Měkota; Memduh Gökırmak; Petr Laitoch

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arXiv · 2008.10392

End to End Dialogue Transformer

Ondřej Měkota·Memduh Gökırmak·Petr Laitoch

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Abstract

Dialogue systems attempt to facilitate conversations between humans and computers, for purposes as diverse as small talk to booking a vacation. We are here inspired by the performance of the recurrent neural network-based model Sequicity, which when conducting a dialogue uses a sequence-to-sequence architecture to first produce a textual representation of what is going on in the dialogue, and in a further step use this along with database findings to produce a reply to the user. We here propose a dialogue system based on the Transformer architecture instead of Sequicity's RNN-based architecture, that works similarly in an end-to-end, sequence-to-sequence fashion.

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BibTeX RIS

Ondřej Měkota, Memduh Gökırmak, Petr Laitoch. 2020-08-24. End to End Dialogue Transformer. https://arxiv.org/abs/2008.10392

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