Content-based Music Information Retrieval includes tasks that involve estimating the pitched content of music, such as the main melody or the bass line. To date, the field lacks a good machine representation that models the human perception of pitch, with each task using specific, tailored representations. This paper proposes factoring pitch estimation problems into two stages, where the output of the first stage for all tasks is a multipitch contour representation. Further, we propose the adoption of \emph{pitch contours} as a unit of pitch organization. We give a review of the existing work on contour extraction and characterization, and present experiments that demonstrate the discriminability of pitch contours. We conclude with directions for future research.

Authors: Bittner, Rachel M.; Salamon, Justin; Bosch, Juan J.; Bello, Juan P.
Affiliations: New York University, New York, NY, USA; Universitat Pompeu Fabra, Barcelona, Spain(See document for exact affiliation information.)
AES Conference: 2017 AES International Conference on Semantic Audio (June 2017)
Paper Number: 3-1
Publication Date: June 13, 2017
Subject: Pitch Tracking

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