Joshua Wissbroecker

Sarah McRoberts, Joshua Wissbroecker, Ruotong Wang et al.

Intelligent agents such as Alexa, Siri, and Google Assistant are now built into streaming TV systems, allowing people to use voice input to navigate the increasingly complex set of apps available on a TV. However, these systems typically support a narrow range of control- and search-oriented commands, and do not support deeper recommendation or exploration queries. To learn about how people interact with a recommendation-oriented voice-controlled TV, we use research through design methods to explore an early prototype movie recommendation system where the only input modality is voice. We describe in-depth qualitative research sessions with 11 participants. We contribute implications for designers of voice-controlled TV: mitigating the drawbacks of voice-only interactions, navigating the tension between expressiveness and efficiency, and building voice-driven recommendation interfaces that facilitate exploration.

Joshua Wissbroecker, F Maxwell Harper

The current generation of streaming media players often allow users to speak commands (e.g., users can change the TV channel by pressing a button and saying "ESPN"). However, these devices typically support a narrow range of control- and search-oriented commands, and do not support deeper recommendation or exploration queries. To study spoken natural language interactions with recommenders, we have built MovieLens TV, a movie recommender system with no input modalities except voice. In this poster, we describe MovieLens TV, with a focus on lessons learned building a prototype system around an off-the-shelf Amazon Echo.