Automatic musical key estimation with adaptive mode bias

Gilberto Bernardes; Matthew E. P. Davies; Carlos Guedes

ICASSP 2017accepted0 citations

Automatic musical key estimation with adaptive mode bias

Gilberto Bernardes, Matthew E. P. Davies, Carlos Guedes

Abstract

In this paper we present the INESC Key Detection (IKD) system which incorporates a novel method for dynamically biasing key mode estimation using the spatial displacement of beat-synchronous Tonal Interval Vectors (TIVs). We evaluate the performance of the IKD system at finding the global key on three annotated audio datasets and using three key-defining profiles. Results demonstrate the effectiveness of the mode bias in favoring either the major or minor mode, thus allowing users to fine tune this variable to improve correct key estimates on style-specific music datasets or to balance predictions across key modes on unknown input sources.

BibTeX

@inproceedings{icassp2017_automaticmusical,
  title = {Automatic musical key estimation with adaptive mode bias},
  author = {Gilberto Bernardes and Matthew E. P. Davies and Carlos Guedes},
  booktitle = {ICASSP 2017},
  year = {2017}
}