Abstract
The study examined humorous interactions with intelligent personal assistants (IPAs, including Google Assistant, Amazon Alexa, Microsoft Cortana, Apple Siri) with the aim of classifying user utterances, IPA responses and user reactions of system responses. Data from online diaries and paper questionnaires were collected and analyzed using content analysis method. The findings suggest that the most frequent types of utterances include questions that test system “personality” and opinions. Joke requests are also frequent and produce pre-programmed humor that users generally find funny. The initial classification of humorous utterances has been validated and expanded using published datasets of humorous utterances for the four investigated IPAs. The findings can be used for immediate improvements to IPA performance as well as long-term development of IPA personas.
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