[4N1-IS-3a] Agents (1/2)

[4N1-IS-3a-01] An Audio Prediction Model for Agents that Prefer Familiar Music

〇Rui Yoshinaga¹, Natsuki Oka¹, Kazuaki Tanaka¹ (1. Kyoto Institute of Technology)

キーワード：generative model, prediction, music, familiarity

Our goal is to build an agent that listens to music with people. We believe that the agent can interact with people more naturally if it has music preferences. Madison and Schiolde (2017) found that repeated listening increases music liking through music listening experiments. The purpose of this study is to build an agent that likes songs it hears repeatedly. We consider the degree of prediction accuracy as the degree of familiarity with a song. The agent listens to a song as raw audio, predicts the song's continuation with a generative model, compares the prediction with the actual input, and judges the music's familiarity. We implemented the agent and investigated its possibility.