Incremental Response Generation Using Prefix-to-Prefix Model for Dialogue System | IEEE Conference Publication | IEEE Xplore

Incremental Response Generation Using Prefix-to-Prefix Model for Dialogue System

Publisher: IEEE

Abstract:

A spoken dialogue system that is currently deployed in many devices cannot respond to a user with a natural switching pause. One of the reasons is that the conventional s...View more

Abstract:

A spoken dialogue system that is currently deployed in many devices cannot respond to a user with a natural switching pause. One of the reasons is that the conventional system generates the response with the pipe-line of several processes, such as speech recognition, response generation, and speech synthesis. The dialogue system should process the user's utterance and generate the response incrementally to achieve natural turn-taking as human-being. In this paper, we examined an incremental response generation method based on a Prefix-to-Prefix model, which is proposed for simultaneous machine translation. This model has a similar structure with the Sequence-to-Sequence model, which is successfully applied to the response generation. We conducted several experiments to confirm the effectiveness of the Prefix-to-Prefix model for incremental response generation.
Date of Conference: 13-16 October 2020
Date Added to IEEE Xplore: 21 December 2020
ISBN Information:
Print on Demand(PoD) ISSN: 2378-8143
Publisher: IEEE
Conference Location: Kobe, Japan

References

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