collaborators

5 papers

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

Deep Neural Network based Distance Estimation for Geometry Calibration in Acoustic Sensor Networks

Tobias Gburrek, Joerg Schmalenstroeer, Andreas Brendel +2

We present an approach to deep neural network based (DNN-based) distance estimation in reverberant rooms for supporting geometry calibration tasks in wireless acoustic sensor netwo…

eess.SP2020

A Unified Bayesian View on Spatially Informed Source Separation and Extraction based on Independent Vector Analysis

Andreas Brendel, Thomas Haubner, Walter Kellermann

Signal separation and extraction are important tasks for devices recording audio signals in real environments which, aside from the desired sources, often contain several interferi…

eess.SP2019

Spatially Informed Independent Vector Analysis

Andreas Brendel, Thomas Haubner, Walter Kellermann

We present a Maximum A Posteriori (MAP) derivation of the Independent Vector Analysis (IVA) algorithm, a blind source separation algorithm, by incorporating a prior over the demixi…