Getting started on computational musicology and music information research: an indian art music perspective

Abstract

Culture-aware and culture-specific approaches to computational musicology and music information research (MIR) have been shown to be effective for analysis of a music culture. Recent efforts as a part of the CompMusic project argued that it is essential to consider the sociocultural specifics of a music tradition to effectively define research problems, collect data and propose methods for analysis. The project also demonstrated the use of such approaches, leading to a collective body of work for MIR in Indian art music. However, it is a considerable effort to define relevant research tasks, collect data and develop specific methods for analysis for each music culture, which often poses a significant entry barrier to start work in the field. One approach in such a scenario is to seek and identify parallel tasks, data and methods from the current state of the art in other music cultures and use them for a preliminary and basic analysis of culturespecific tasks, extending them with culture-specific methods to be more effective and relevant. While it is a sub-optimal compromise, such a perspective will enable preliminary analysis of a music culture using existing methods, and integrate it as a use-case with existing common frameworks and approaches in MIR and data-driven computational musicology. In this chapter, we aid such an approach by describing common concepts, frameworks, approaches, resources, data and methods for computational analysis of music from a perspective that could be useful for the analysis of Indian Art music. With this perspective, it is hypothesized that the currently established methods and tools, along with the datasets and corpora built within the CompMusic project will encourage accelerated research into different research problems relevant to Indian art music. The content of the chapter is targeted at musicians, music students, technology enthusiasts, engineers and researchers to provide them a context of the current state of the art that could help them start their work with computational analysis of Indian art music.