You are currently logged in as an
Institutional Subscriber.
If you would like to logout,
please click on the button below.
Home / Publications / E-library page
Only AES members and Institutional Journal Subscribers can download
For blind source separation, the non-negative matrix factorization extracts single notes out of a mixture. These notes can be clustered to form the melodies played by a single instrument. A current approach for clustering utilizes a source filter model to describe the envelope over the first dimension of the spectrogram: the frequency-axis. The novelty of this paper is to extend this approach by a second source-filter model, characterizing the second dimension of a spectrogram: the time-axis. The latter one models the temporal evolution of the energy of one note: an instrument specific envelope is convolved with an activation vector, corresponding to tempo, rhythm, and amplitudes of single note instances. We introduce an unsupervised clustering framework for both models and a simple, yet effective combination strategy. Finally, we show the advantages of our separation algorithm compared with two other state-of-the-art separation frameworks: the separation quality is comparable, but our algorithm needs much less computational load, is independent from other BSS-algorithm as initialization, and works with a unique set of parameters for a wide range of audio data.
Author (s): Spiertz, Martin; Gnann, Volker
Affiliation:
RWTH Aachen University, Aachen, Germany
(See document for exact affiliation information.)
Publication Date:
2011-07-06
Import into BibTeX
Session subject:
Automatic Music Transcription
Permalink: https://aes2.org/publications/elibrary-page/?id=15941
(2617KB)
Click to purchase paper as a non-member 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 Join the AES. If you need to check your member status, login to the Member Portal.
Spiertz, Martin; Gnann, Volker; 2011; Note Clustering Based on 2-D Source-Filter Modeling for Underdetermined Blind Source Separation [PDF]; RWTH Aachen University, Aachen, Germany; Paper 3-2; Available from: https://aes2.org/publications/elibrary-page/?id=15941
Spiertz, Martin; Gnann, Volker; Note Clustering Based on 2-D Source-Filter Modeling for Underdetermined Blind Source Separation [PDF]; RWTH Aachen University, Aachen, Germany; Paper 3-2; 2011 Available: https://aes2.org/publications/elibrary-page/?id=15941