Computer-Aided Analysis and Pedagogy: Algorithmic Harmony and Voice Leading

Rachel Mitchell, Univ. of Texas, Rio Grande Valley

This poster introduces a computer application that can assess multi-part, tonal music scores and parse them into harmonic chord structures and analyze contrapuntal motions and voice leading. The app analyzes music using essentially the same rules and guidelines we teach our students to gain a basic understanding of tonal musical practice. It can determine key areas and modulations, harmonic functions, diatonic and chromatic harmonies and non-harmonic tones, interval sizes and qualities, and find voice-leading errors such as parallel octaves, voice crossing, doubled leading tones, and more. The app contains as its in-app corpus the 371 harmonized chorales by J. S. Bach, which may also be searched for sonorities or voice-leading errors.

By combining such technology with a user-friendly, graphical interface, music scholars with even the most limited computer skills can easily navigate the app and use its analytical tools to conduct corpus-based studies such as those found in Tymoczko, Quinn, and White. Such technology also has applications in music pedagogy, whereby teachers can create interactive assignments resembling those found in any textbook or workbook and students can practice analysis and part-writing concepts and receive immediate computer-generated feedback. The poster also shares data from a 2015 NSF-funded experiment of Theory 1 students at a large R1-university, who benefited from their consistent use of the software for homework and practice for an entire semester.