Adaptive filtering algorithms are pervasive throughout signal processing and have had a
material impact on a wide variety of domains including audio processing …

While existing end-to-end beamformers achieve impressive performance in various front-
end speech processing tasks, they usually encapsulate the whole process into a black box …

In this paper, we present a sound field interpolation for array signal processing (ASP) that is
robust to rotation of a circular microphone array (CMA), and we evaluate beamforming as …

We introduce a new online adaptive filtering method called supervised multi-step adaptive
filters (SMS-AF). Our method uses neural networks to control or optimize linear multi-delay …

Current multichannel speech enhancement algorithms typically assume a stationary sound
source, a common mismatch with reality that limits their performance in real-world scenarios …

Adaptive filters (AFs) are vital for enhancing the performance of downstream tasks, such as
speech recognition, sound event detection, and keyword spotting. However, traditional AF …

This paper introduces an explainable DNN-based beamformer with a postfilter (ExNet-BF+
PF) for multichannel signal processing. Our approach combines the U-Net network with a …

This paper presents a unified model for combining beamforming and blind source
separation (BSS). The validity of the model's assumptions is confirmed by recovering target …

Adaptive filters are applicable to many signal processing tasks including acoustic echo
cancellation, beamforming, and more. Adaptive filters are typically controlled using …

Spatial room impulse responses (SRIRs) facilitate the rendering of virtual sound sources to
realistically augment a real-world acoustic scene, for example in the context of augmented …