By Topic

SVD-based polyphonic music transcription

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
İsmail Arı ; Bilgisayar Mühendisliği Bölümü, Boğaziçi Üniversitesi, 34342 Bebek, İstanbul, Turkey ; Umut Şimşekli ; Ali Taylan Cemgil ; Lale Akarun

The aim of this work is to perform polyphonic music transcription in an efficient way. The problem is formulated as a linear model and the speed is improved by a randomized SVD-based method. The method is shown to compete with the best resulting approaches in literature. The conventional methods seem to fail in this era of big data whereas the proposed method efficiently handles this by use of randomized algorithms for matrix decompositions. The method is able to improve time and space complexity without compromising the high success rate.

Published in:

2012 20th Signal Processing and Communications Applications Conference (SIU)

Date of Conference:

18-20 April 2012