48 citations · 97 across the 15 of their papers we have counts for
16 papers
End-To-End Deep Learning-based Adaptation Control for Linear Acoustic Echo Cancellation
Thomas Haubner, Andreas Brendel, Walter Kellermann
The attenuation of acoustic loudspeaker echoes remains to be one of the open challenges to achieve pleasant full-duplex hands free speech communication. In many modern signal enhan…
A Unifying View on Blind Source Separation of Convolutive Mixtures based on Independent Component Analysis
Andreas Brendel, Thomas Haubner, Walter Kellermann
In many daily-life scenarios, acoustic sources recorded in an enclosure can only be observed with other interfering sources. Hence, convolutive Blind Source Separation (BSS) is a c…
Microphone Utility Estimation in Acoustic Sensor Networks using Single-Channel Signal Features
Michael Günther, Andreas Brendel, Walter Kellermann
In multichannel signal processing with distributed sensors, choosing the optimal subset of observed sensor signals to be exploited is crucial in order to maximize algorithmic perfo…
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).…
End-To-End Deep Learning-Based Adaptation Control for Frequency-Domain Adaptive System Identification
Thomas Haubner, Andreas Brendel, Walter Kellermann
We present a novel end-to-end deep learning-based adaptation control algorithm for frequency-domain adaptive system identification. The proposed method exploits a deep neural netwo…
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…