| bibtype |
J -
Journal Article
|
| ARLID |
0356661 |
| utime |
20240903175012.6 |
| mtime |
20110228235959.9 |
| WOS |
000291717600016 |
| SCOPUS |
84907567733 |
| DOI |
10.1109/TASL.2010.2049411 |
| title
(primary) (eng) |
Time-Domain Blind Separation of Audio Sources on the Basis of a Complete ICA Decomposition of an Observation Space |
| specification |
|
| serial |
| ARLID |
cav_un_epca*0311609 |
| ISSN |
1558-7916 |
| title
|
IEEE Transactions on Audio Speech and Language Processing |
| volume_id |
19 |
| volume |
2 (2011) |
| page_num |
406-416 |
|
| keyword |
blind source separation |
| keyword |
audio |
| keyword |
speech |
| author
(primary) |
| ARLID |
cav_un_auth*0108100 |
| name1 |
Koldovský |
| name2 |
Zbyněk |
| full_dept (cz) |
Stochastická informatika |
| full_dept (eng) |
Department of Stochastic Informatics |
| department (cz) |
SI |
| department (eng) |
SI |
| institution |
UTIA-B |
| full_dept |
Department of Stochastic Informatics |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101212 |
| name1 |
Tichavský |
| name2 |
Petr |
| full_dept (cz) |
Stochastická informatika |
| full_dept |
Department of Stochastic Informatics |
| department (cz) |
SI |
| department |
SI |
| institution |
UTIA-B |
| full_dept |
Department of Stochastic Informatics |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
1M0572 |
| agency |
GA MŠk |
| ARLID |
cav_un_auth*0001814 |
|
| project |
| project_id |
GP102/07/P384 |
| agency |
GAČR |
| country |
CZ |
| ARLID |
cav_un_auth*0227962 |
|
| project |
| project_id |
GA102/09/1278 |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0253174 |
|
| research |
CEZ:AV0Z10750506 |
| abstract
(eng) |
A novel time-domain algorithm for blind separation of audio sources that is based on a complete unconstrained decomposition of the observation space is proposed. The observation space may be defined in a general way, which allows application of long separating filters, although its dimension is low. The decomposition is done by an appropriate independent component analysis (ICA) algorithm giving independent components that are grouped into clusters corresponding to the original sources. Components of the clusters are combined by a reconstruction procedure after estimating responses of the original sources. The authors demonstrate by experiments that the method works effectively with short data, compared to other methods. |
| reportyear |
2011 |
| RIV |
BI |
| mrcbC52 |
4 A 4a 20231122134443.4 |
| permalink |
http://hdl.handle.net/11104/0195125 |
| mrcbT16-e |
ACOUSTICS|ENGINEERINGELECTRICALELECTRONIC |
| mrcbT16-f |
1.962 |
| mrcbT16-g |
0.305 |
| mrcbT16-h |
4.1 |
| mrcbT16-i |
0.01048 |
| mrcbT16-j |
0.659 |
| mrcbT16-k |
1779 |
| mrcbT16-l |
203 |
| mrcbT16-s |
0.892 |
| mrcbT16-4 |
Q1 |
| mrcbT16-B |
62.973 |
| mrcbT16-C |
66.276 |
| mrcbT16-D |
Q2 |
| mrcbT16-E |
Q2 |
| arlyear |
2011 |
| mrcbTft |
\nSoubory v repozitáři: tichavsky-0356661.pdf |
| mrcbU14 |
84907567733 SCOPUS |
| mrcbU34 |
000291717600016 WOS |
| mrcbU63 |
cav_un_epca*0311609 IEEE Transactions on Audio Speech and Language Processing 1558-7916 1558-7924 Roč. 19 č. 2 2011 406 416 |
|