Zobrazeno 1 - 10
of 436
pro vyhledávání: '"P. Koldovský"'
Non-Gaussianity-based Independent Vector Extraction leads to the famous one-unit FastICA/FastIVA algorithm when the likelihood function is optimized using an approximate Newton-Raphson algorithm under the orthogonality constraint. In this paper, we r
Externí odkaz:
http://arxiv.org/abs/2407.09259
Independent Vector Analysis (IVA) is a popular extension of Independent Component Analysis (ICA) for joint separation of a set of instantaneous linear mixtures, with a direct application in frequency-domain speaker separation or extraction. The mixtu
Externí odkaz:
http://arxiv.org/abs/2304.01778
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 pa
Externí odkaz:
http://arxiv.org/abs/2212.01178
We describe a joint acoustic echo cancellation (AEC) and blind source extraction (BSE) approach for multi-microphone acoustic frontends. The proposed algorithm blindly estimates AEC and beamforming filters by maximizing the statistical independence o
Externí odkaz:
http://arxiv.org/abs/2205.06473
In this article, nonstationary mixing and source models are combined for developing new fast and accurate algorithms for Independent Component or Vector Extraction (ICE/IVE), one of which stands for a new extension of the well-known FastICA. This mod
Externí odkaz:
http://arxiv.org/abs/2204.04992
Autor:
Malek, Jiri, Jansky, Jakub, Koldovsky, Zbynek, Kounovsky, Tomas, Cmejla, Jaroslav, Zdansky, Jindrich
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 30, pp. 2295-2309, 2022
This manuscript proposes a novel robust procedure for the extraction of a speaker of interest (SOI) from a mixture of audio sources. The estimation of the SOI is performed via independent vector extraction (IVE). Since the blind IVE cannot distinguis
Externí odkaz:
http://arxiv.org/abs/2111.03482
A novel extension of Independent Component and Independent Vector Analysis for blind extraction/separation of one or several sources from time-varying mixtures is proposed. The mixtures are assumed to be separable source-by-source in series or in par
Externí odkaz:
http://arxiv.org/abs/2007.11241
Recently, Constant Separating Vector (CSV) mixing model has been proposed for the Blind Source Extraction (BSE) of moving sources. In this paper, we experimentally verify the applicability of CSV in the blind extraction of a moving speaker and propos
Externí odkaz:
http://arxiv.org/abs/2002.12619
Adaptive blind audio source extraction supervised by dominant speaker identification using x-vectors
Autor:
Janský, Jakub, Málek, Jiří, Čmejla, Jaroslav, Kounovský, Tomáš, Koldovský, Zbyněk, Žďánský, Jindřich
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 superv
Externí odkaz:
http://arxiv.org/abs/1910.11824
A new algorithm for dynamic independent vector extraction is proposed. It is based on the mixing model where mixing parameters related to the source-of-interest (SOI) are time-variant while the separating parameters are time-invariant. A contrast fun
Externí odkaz:
http://arxiv.org/abs/1910.10242