#4191. A geometric framework for pitch estimation on acoustic musical signals

September 2026publication date
Proposal available till 27-05-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Music;
Applied Mathematics;
Computational Mathematics;
Modeling and Simulation;
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Abstract:
This paper presents a geometric approach to pitch estimation (PE)–an important problem in music information retrieval (MIR), and a precursor to a variety of other problems in the field. Though there exist a number of highly accurate methods, both mono-pitch estimation and multi-pitch estimation (particularly with unspecified polyphonic timbre) prove computationally and conceptually challenging. Tackling the approach from both theoretical and experimental perspectives, we present a novel framework, a basis for further work in the area, and results that (while not state of the art) demonstrate relative efficacy. The framework presented in this paper opens up a completely new way to tackle PE problems and may have uses both in traditional analytical approaches as well as in the emerging machine learning (ML) methods that currently dominate the literature.
Keywords:
Geometry; music information retrieval; pitch estimation; signal processing; visualization

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