2019/06/03 by Xu Han, Han, Xu, Tom Yeh +1
Computer Science · Psychology · #AI in Service Interactions #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Social Robot Interaction and HRI #Speech and dialogue systems #cs.HC
paper · pdf · doi:10.48550/arxiv.1906.01122
11 pages, 3 figures
arxiv created 2019/06/03 · openalex publication_date 2019/06/03 · arxiv updated 2019/06/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Currently, adaptive voice applications supported by voice assistants (VA) are very popular (i.e., Alexa skills and Google Home Actions). Under this circumstance, how to design and evaluate these voice interactions well is very important. In our study, we developed a voice crawler to collect responses from 100 most popular Alexa skills under 10 different categories and evaluated these responses to find out how they comply with 8 selected design guidelines published by Amazon. Our findings show that basic commands support are the most followed ones while those related to personalised interaction are relatively less. There also exists variation in design guidelines compliance across different skill categories. Based on our findings and real skill examples, we offer suggestions for new guidelines to complement the existing ones and propose agendas for future HCI research to improve voice applications' user experiences.