Visualizing the Semantics of Music

We introduce SongVis, a visualization that represents music's semantic descriptors. SongVis uses emojis, colors, lines and shapes to embody the semantic content of a song. It aims to aid users on tasks related to exploration/browsing of music libraries and at queries for similar tracks based on visual characteristics. We first collected the descriptors after surveying papers on the topic of "music visualization", and used a questionnaire to rank the terms by consulting the public. Then, the features: mood, danceability, tempo, music genre and instrument, were extracted using state-of-the-art music information retrieval algorithms and we considered their visuals. Then, we discuss potential improvements to be made. With SongVis we perform a step forward towards visually representing semantic descriptors and expect that the music information research, the information visualization fields and the public can benefit from this work.