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20192021
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eess.AS2021

Manifold learning-supported estimation of relative transfer functions for spatial filtering

Andreas Brendel, Johannes Zeitler, Walter Kellermann

Many spatial filtering algorithms used for voice capture in, e.g., teleconferencing applications, can benefit from or even rely on knowledge of Relative Transfer Functions (RTFs).…

eess.AS2021

Online Acoustic System Identification Exploiting Kalman Filtering and an Adaptive Impulse Response Subspace Model

Thomas Haubner, Andreas Brendel, Walter Kellermann

We introduce a novel algorithm for online estimation of acoustic impulse responses (AIRs) which allows for fast convergence by exploiting prior knowledge about the fundamental stru…

eess.AS2020

Misalignment Recognition in Acoustic Sensor Networks using a Semi-supervised Source Estimation Method and Markov Random Fields

Gabriel F Miller, Andreas Brendel, Walter Kellermann +1

In this paper, we consider the problem of acoustic source localization by acoustic sensor networks (ASNs) using a promising, learning-based technique that adapts to the acoustic en…

eess.AS2020

Accelerating Auxiliary Function-based Independent Vector Analysis

Andreas Brendel, Walter Kellermann

Independent Vector Analysis (IVA) is an effective approach for Blind Source Separation (BSS) of convolutive mixtures of audio signals. As a practical realization of an IVA-based BS…

eess.AS2020

Online Supervised Acoustic System Identification exploiting Prelearned Local Affine Subspace Models

Thomas Haubner, Andreas Brendel, Walter Kellermann

In this paper we present a novel algorithm for improved block-online supervised acoustic system identification in adverse noise scenarios by exploiting prior knowledge about the sp…

eess.AS2020

Noise-Robust Adaptation Control for Supervised Acoustic System Identification Exploiting A Noise Dictionary

Thomas Haubner, Andreas Brendel, Mohamed Elminshawi +1

We present a noise-robust adaptation control strategy for block-online supervised acoustic system identification by exploiting a noise dictionary. The proposed algorithm takes adva…