Investigating the Role of Score Following in Automatic Musical Accompaniment

Abstract

When suitable accompanists are not available to a soloist musician, an alternative possibility is to use computer-generated accompaniment. A computer accompanist should interact with the soloist and adapt to the soloist's playing as a human accompanist would, both reacting to expressive nuances of tempo and to unintentional errors such as wrong or mistimed notes. Over the past 25 years, accompaniment systems have been developed, all of which employ some form of score following: the process of following a musician's progress through the score of a piece during performance. This work considers the role of score following in automatic accompaniment. In this investigation we developed a computer accompanist that employs score following. Our computer musician uses Hidden Markov Models to model the score by metrical structure and to provide accompaniment to a soloist playing monophonic music in real time, as the soloist is playing. Working with MIDI input/output, it tracks tempo fluctuations, anticipates the soloist's next note and supports some amount of unintentional deviation from the score. Qualitative evaluation, by human testers, and quantitative evaluation, using measurable criteria taken from MIREX, reported that the system performs adequately. We then used interviews with eight human accompanists to consider how well a score following system models the accompaniment process. This evaluation raises questions about the musical interaction between soloist and accompanist that have received relatively little attention. The information we gathered from interviews suggests the importance of other aspects of accompaniment, such as the sharing of shape of the performance between musicians, rather than treating the accompanist as purely subservient. We discuss the implications of these issues for the design of automated accompanists.

Acknowledgements

We thank Kinnell Anderson, Peter Nelson, Dave Murray-Rust, Nick Collins and Christopher Raphael for their advice and practical help. The comments from two anonymous reviewers, from Emilios Cambouropoulos and from the participants at the Conference for Interdisciplinary Musicology were also very useful.

Those who tested the accompaniment system gave valuable feedback. Similarly the knowledge and experience of the accompanists whom we interviewed played an instrumental part in placing this work in a wider context.

Notes

¹Orio et al. (2003) describe score following systems taking a note-based approach.

²MIREX did not host a Score Following task in 2007.

³We make no claims here for how an artificial accompanist should best react in the event of a fire alarm.

⁴Speckled computing project homepage: http://www.specknet. org/, retrieved April 2009.

⁵The MIREX abstract for Montecchio and Orio's system was unavailable on the MIREX website at the time of submitting this paper.