TY - GEN
T1 - Semi-blind source separation via sparse representations and online dictionary learning
AU - Rambhatla, Sirisha
AU - Haupt, Jarvis
PY - 2013
Y1 - 2013
N2 - This work examines a semi-blind single-channel source separation problem. Our specific aim is to separate one source whose local structure is approximately known, from another a priori unspecified background source, given only a single linear combination of the two sources. We propose a separation technique based on local sparse approximations along the lines of recent efforts in sparse representations and dictionary learning. A key feature of our procedure is the online learning of dictionaries (using only the data itself) to sparsely model the background source, which facilitates its separation from the partially-known source. Our approach is applicable to source separation problems in various application domains; here, we demonstrate the performance of our proposed approach via simulation on a stylized audio source separation task.
AB - This work examines a semi-blind single-channel source separation problem. Our specific aim is to separate one source whose local structure is approximately known, from another a priori unspecified background source, given only a single linear combination of the two sources. We propose a separation technique based on local sparse approximations along the lines of recent efforts in sparse representations and dictionary learning. A key feature of our procedure is the online learning of dictionaries (using only the data itself) to sparsely model the background source, which facilitates its separation from the partially-known source. Our approach is applicable to source separation problems in various application domains; here, we demonstrate the performance of our proposed approach via simulation on a stylized audio source separation task.
KW - Source separation
KW - dictionary learning
KW - sparse representations
UR - http://www.scopus.com/inward/record.url?scp=84901255196&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84901255196&partnerID=8YFLogxK
U2 - 10.1109/ACSSC.2013.6810587
DO - 10.1109/ACSSC.2013.6810587
M3 - Conference contribution
AN - SCOPUS:84901255196
SN - 9781479923908
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 1687
EP - 1691
BT - Conference Record of the 47th Asilomar Conference on Signals, Systems and Computers
PB - IEEE Computer Society
T2 - 2013 47th Asilomar Conference on Signals, Systems and Computers
Y2 - 3 November 2013 through 6 November 2013
ER -