Katariina Martikainen, Jussi Karlgren, Khiet Truong
Giving Voice to Silent Data: Designing with Personal Music Listening History
Music streaming services collect listener data to support personalization and discovery of their extensive catalogs. Yet this data is typically used in ways that are not immediately apparent to listeners. We conducted design workshops with ten Spotify listeners to imagine future voice assistant (VA) interactions leveraging logged music data. We provided participants with detailed personal music listening data, such as play-counts and temporal patterns, which grounded their design ideas in their current behaviors. In the interactions participants designed, VAs did not simply speak their data out loud; instead, participants envisioned how data could implicitly support introspection, behavior change, and exploration. We present reflections on how VAs could evolve from voice-activated remote controls to intelligent music coaches and how personal data can be leveraged as a design resource.
TastePaths: Enabling deeper exploration and understanding of personal preferences in recommender systems
Saavas Petridis, Nediyana Daskalova, Sarah Mennicken, Samuel F. Way, Paul Lamere, Jennifer Thom
Ziang Xiao, Sarah Mennicken, Bernd Huber, Adam Shonkoff, Jennifer Thom