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Improving automatic music transcription through key detection

Benetos, E., Jansson, A. and Weyde, T. (2014). Improving automatic music transcription through key detection. Paper presented at the AES 53rd International Conference on Semantic Audio, 27 - 29 Jan 2014, London, UK.

Abstract

In this paper, a method for automatic transcription of polyphonic music is proposed that exploits key information. The proposed system performs key detection using a matching technique with distributions of pitch class pairs, called Zweiklang profiles. The automatic transcription system is based on probabilistic latent component analysis, supporting templates from multiple instruments, as well as tuning deviations and frequency modulations. Key information is incorporated to the transcription system using Dirichlet priors during the parameter update stage. Experiments are performed on a polyphonic, multiple-instrument dataset of Bach chorales, where it is shown that incorporating key information improves multi-pitch detection and instrument assignment performance.

Publication Type: Conference or Workshop Item (Paper)
Subjects: M Music and Books on Music > M Music
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Mathematics, Computer Science & Engineering > Computer Science
Related URLs:
URI: http://openaccess.city.ac.uk/id/eprint/3162
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