Scheduled System Maintenance:
On Monday, April 27th, IEEE Xplore will undergo scheduled maintenance from 1:00 PM - 3:00 PM ET (17:00 - 19:00 UTC). No interruption in service is anticipated.
By Topic

A Musically Motivated Mid-Level Representation for Pitch Estimation and Musical Audio Source Separation

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
$31 $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

3 Author(s)
Durrieu, J. ; Signal Process. Labs. (LTS5), Ecole Polytech. Fed. de Lausanne (EPFL), Lausanne, Switzerland ; David, B. ; Richard, G.

When designing an audio processing system, the target tasks often influence the choice of a data representation or transformation. Low-level time-frequency representations such as the short-time Fourier transform (STFT) are popular, because they offer a meaningful insight on sound properties for a low computational cost. Conversely, when higher level semantics, such as pitch, timbre or phoneme, are sought after, representations usually tend to enhance their discriminative characteristics, at the expense of their invertibility. They become so-called mid-level representations. In this paper, a source/filter signal model which provides a mid-level representation is proposed. This representation makes the pitch content of the signal as well as some timbre information available, hence keeping as much information from the raw data as possible. This model is successfully used within a main melody extraction system and a lead instrument/accompaniment separation system. Both frameworks obtained top results at several international evaluation campaigns.

Published in:

Selected Topics in Signal Processing, IEEE Journal of  (Volume:5 ,  Issue: 6 )