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Jaroslav Cmejla

3 accepted papers

2023

Dynamic Independent Component Extraction with Blending Mixing Vector: Lower Bound on Mean Interference-to-Signal Ratio

ICASSP 2023accepted

This paper deals with dynamic Blind Source Extraction (BSE) from where the mixing parameters characterizing the position of a source of interest (SOI) are allowed to vary over time. We present a new source extraction model called CvxCSV which is a parameter-reduced modification of the recent Constan…

Cited by 0SourceScholar
2021

Blind Extraction of Moving Sources via Independent Component and Vector Analysis: Examples

ICASSP 2021accepted

This paper is devoted to the recently proposed mixing model with constant separating vector (CSV) for Blind Source Extraction of moving sources using the FastDIVA algorithm, which is an extension of the famous FastICA and FastIVA for static mixtures. The benefits due to the CSV model and FastDIVA ar…

Cited by 0SourceScholar
2020

Adaptive Blind Audio Source Extraction Supervised By Dominant Speaker Identification Using X-Vectors

ICASSP 2020accepted

We propose a novel algorithm for adaptive blind audio source extraction. The proposed method is based on independent vector analysis and utilizes the auxiliary function optimization to achieve high convergence speed. The algorithm is partially supervised by a pilot signal related to the source of in…

Cited by 0SourceScholar