The talk is about Pitch Analysis for Active Music Discovery:
A significant proportion of commercial music is comprised of pitched content: a melody, a bass line, a famous guitar solo, etc. Consequently, algorithms that are capable of extracting and understanding this type of pitched content open up numerous opportunities for active music discovery, ranging from query-by-humming to musical-feature-based exploration of Indian art music or recommendation based on singing style. In this talk I will describe some of my work on algorithms for pitch content analysis of music audio signals and their application to music discovery, the role of machine learning in these algorithms, and the challenge posed by the scarcity of labeled data and how we may address it.
And here's the extended abstract:
Pitch Analysis for Active Music Discovery
Machine Learning for Music Discovery workshop, International Conference on Machine Learning (ICML), invited talk, New York City, NY, USA, June 2016.
The workshop has a great program lined up, if your'e attending ICML 2016 be sure to drop by!