AES E-Library

A Robust Partial Tracker for Analysis of Music Signals

We propose a novel approach for tracking of partials in music signals based on a robust Kalman filter. The tracker is based on a regularized least-squares approach that is designed to minimize the worst-possible regularized residual norm over the class of admissible uncertainties at each iteration. We introduce a set of state-space models for our signals based on the evolution of frequency and amplitude in different classes of musical instruments. These prior models are used to estimate future values of partial tracks in successive time frames of our spectral data. Here, the parameters of evolution models are treated as bounded uncertainties and our tracker can robustly track both frequency and power partials in all frequency regions.

Authors: Satar-Boroujeni, Hamid; Shafai, Bahram
Affiliation: Northeastern University
AES Convention:119 (October 2005) Paper Number:6566 Import into BibTeX
Subject:Miscellaneous Audio Topics

Click to purchase paper or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!

This paper costs $20 for non-members, $5 for AES members and is free for E-Library subscribers.

Learn more about the AES E-Library

E-Library Location: (CD 119Papers)   /119/6566.pdf

Start a discussion about this paper!