What Do You Mean I'm Funny? Personalizing the Joke Skill of a Voice-Controlled Virtual Assistant

A considerable part of the success experienced by Voice-controlled virtual assistants (VVA) is due to the emotional and personalized experience they deliver, with humor being a key component in providing an engaging interaction. In this paper we describe methods used to improve the joke skill of a V...

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Bibliographic Details
Published inarXiv.org
Main Authors Mottini, Alejandro, Amber Roy Chowdhury
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 06.12.2019
Subjects
Feedback
Heuristic methods
Labels
Learning
User satisfaction
Voice control
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Summary:A considerable part of the success experienced by Voice-controlled virtual assistants (VVA) is due to the emotional and personalized experience they deliver, with humor being a key component in providing an engaging interaction. In this paper we describe methods used to improve the joke skill of a VVA through personalization. The first method, based on traditional NLP techniques, is robust and scalable. The others combine self-attentional network and multi-task learning to obtain better results, at the cost of added complexity. A significant challenge facing these systems is the lack of explicit user feedback needed to provide labels for the models. Instead, we explore the use of two implicit feedback-based labelling strategies. All models were evaluated on real production data. Online results show that models trained on any of the considered labels outperform a heuristic method, presenting a positive real-world impact on user satisfaction. Offline results suggest that the deep-learning approaches can improve the joke experience with respect to the other considered methods.
ISSN:2331-8422