2022
DOI: 10.17743/jaes.2022.0030
|View full text |Cite
|
Sign up to set email alerts
|

Conditioned Source Separation by Attentively Aggregating Frequency Transformations With Self-Conditioning

Abstract: Label-conditioned source separation extracts the target source, specified by an input symbol, from an input mixture track. A recently proposed label-conditioned source separation model called Latent Source Attentive Frequency Transformation (LaSAFT)-Gated Point-Wise Convolutional Modulation (GPoCM)-Net introduced a block for latent source analysis called LaSAFT. Employing LaSAFT blocks, it established state-of-the-art performance on several tasks of the MUSDB18 benchmark. This paper enhances the LaSAFT block b… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 26 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?