Keynote: Deep learning for audio-based music recommendation

The advent of deep learning has made it possible to extract high-level information from perceptual signals without having to specify manually and explicitly how to obtain it; instead, this can be learned from examples. This creates opportunities for automated content analysis of musical audio signals. In this talk, I will discuss how deep learning techniques can be used for audio-based music recommendation, with which we can tackle the item cold-start problem that burdens the prevailing collaborative filtering approaches.