Music Information Research Based on Machine Learning by Masataka Goto and Kazuyoshi Yoshii.
From the webpage:
Music information research is gaining a lot of attention after 2000 when the general public started listening to music on computers in daily life. It is widely known as an important research field, and new researchers are continually joining the field worldwide. Academically, one of the reasons many researchers are involved in this field is that the essential unresolved issue is the understanding of complex musical audio signals that convey content by forming a temporal structure while multiple sounds are interrelated. Additionally, there are still appealing unresolved issues that have not been touched yet, and the field is a treasure trove of research topics that could be tackled with state-of-the-art machine learning techniques.
This tutorial is intended for an audience interested in the application of machine learning techniques to such music domains. Audience members who are not familiar with music information research are welcome, and researchers working on music technologies are likely to find something new to study.
First, the tutorial serves as a showcase of music information research. The audience can enjoy and study many state-of-the-art demonstrations of music information research based on signal processing and machine learning. This tutorial highlights timely topics such as active music listening interfaces, singing information processing systems, web-related music technologies, crowdsourcing, and consumer-generated media (CGM).
Second, this tutorial explains the music technologies behind the demonstrations. The audience can learn how to analyze and understand musical audio signals, process singing voices, and model polyphonic sound mixtures. As a new approach to advanced music modeling, this tutorial introduces unsupervised music understanding based on nonparametric Bayesian models.
Third, this tutorial provides a practical guide to getting started in music information research. The audience can try available research tools such as music feature extraction, machine learning, and music editors. Music databases and corpora are then introduced. As a hint towards research topics, this tutorial also discusses open problems and grand challenges that the audience members are encouraged to tackle.
In the future, music technologies, together with image, video, and speech technologies, are expected to contribute toward all-around media content technologies based on machine learning.
Always nice to start with week with something different.
I first saw this in a tweet by Masataka Goto.