2020
DOI: 10.48550/arxiv.2002.12619
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Auxiliary Function-Based Algorithm for Blind Extraction of a Moving Speaker

Abstract: Independent Vector Extraction (IVE) is a modification of Independent Vector Analysis (IVA) for Blind Source Extraction (BSE) to a setup in which only one source of interest (SOI) should be separated from a mixture of signals observed by microphones. The fundamental assumption is that the SOI is independent of the other signals. IVE shows reasonable results; however, its basic variant is limited to static sources. To extract a moving source, IVE has recently been extended by considering the Constant Separating … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

0
4
0

Year Published

2021
2021
2021
2021

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(4 citation statements)
references
References 38 publications
0
4
0
Order By: Relevance
“…The extraction part of the proposed procedure is a blind algorithm based on the CSV mixing model. The algorithm was derived in [28]; let us overview its most important ideas. The CSV model is based on an assumption that the separating vector w k t is constant within all T blocks (w k t = w k , t = 1 .…”
Section: B Blind Extraction: Csv-auxive Algorithmmentioning
confidence: 99%
See 3 more Smart Citations
“…The extraction part of the proposed procedure is a blind algorithm based on the CSV mixing model. The algorithm was derived in [28]; let us overview its most important ideas. The CSV model is based on an assumption that the separating vector w k t is constant within all T blocks (w k t = w k , t = 1 .…”
Section: B Blind Extraction: Csv-auxive Algorithmmentioning
confidence: 99%
“…Using the assumption that all samples are independently distributed, the log-likelihood function (4) can be averaged over all blocks and samples. Following the derivations from [28], the contrast function is obtained in the form…”
Section: B Blind Extraction: Csv-auxive Algorithmmentioning
confidence: 99%
See 2 more Smart Citations