Some Thoughts on the How, What and Why of Music Informatics Research
The framework of music informatics research (MIR) can be thought of as a closed loop of data collection, algorithmic development and benchmarking. Much of what we do is heavily focused on the algorithmic aspects, or how to optimally combine various techniques from e.g., signal processing, data mining, and machine learning, to solve a variety of problems that captivate the interest of our community. We are very good at this, and in this talk I will describe some of the know-how that we have collectively accumulated over the years. On the other hand, I would argue that data collection and benchmarking have received far less attention and are often treated as afterthoughts, and that we sometimes tend to rely on widespread and limiting assumptions about music that affect the validity and usability of our research. I will end with a discussion of a few ideas intended to bring humans into the MIR loop as a potential solution to these shortcomings.