CUED Publications database

Bayesian estimation of simultaneous musical notes based on frequency domain modelling

Kashino, K and Godsill, SJ (2004) Bayesian estimation of simultaneous musical notes based on frequency domain modelling. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 4. IV-305-IV-308. ISSN 1520-6149

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Abstract

This paper proposes a Bayesian method for polyphonic music description. The method first divides an input audio signal into a series of sections called snapshots, and then estimates parameters such as fundamental frequencies and amplitudes of the notes contained in each snapshot. The parameter estimation process is based on a frequency domain modelling and Gibbs sampling. Experimental results obtained from audio signals of test note patterns are encouraging; the accuracy is better than 80% for the estimation of fundamental frequencies in terms of semitones and instrument names when the number of simultaneous notes is two.

Item Type: Article
Subjects: UNSPECIFIED
Divisions: Div F > Signal Processing and Communications
Depositing User: Cron Job
Date Deposited: 07 Mar 2014 12:20
Last Modified: 08 Dec 2014 02:29
DOI: