9 accepted papers
Diffusion models are a new class of generative models that have recently been applied to speech enhancement successfully. Previous works have demonstrated their superior performance in mismatched conditions compared to state-of-the art discriminative models. However, this was investigated with a sin…
In this paper, we propose the use of self-supervised pretraining on a large unlabelled data set to improve the performance of a personalized voice activity detection (VAD) model in adverse conditions. We pretrain a long short-term memory (LSTM)-encoder using the autoregressive predictive coding (APC…
Speech enhancement in hearing aids (HAs) can take advantage of a wireless remote microphone (RM) having a better signal-to-noise ratio than the HA microphones. However, using the RM effectively is complicated by the time delay between the acoustic and wireless signals. Methods in the literature assu…
Distributed signal-processing algorithms in (wireless) sensor networks often aim to decentralize processing tasks to reduce communication cost and computational complexity or avoid reliance on a single device (i.e., fusion center) for processing. In this contribution, we extend a distributed adaptiv…
Extracting information from fMRI data constitutes a broad active area of research. Current techniques still present several limitations; some ignore relevant aspects regarding the brain functioning or lack of interpretability. In an effort to overcome such limitations, we introduce an extension of t…
Low frequency personal sound zones can be created by controlling the sound pressure in separate spatially confined regions. The performance of a sound zone system using wireless communication may be degraded due to potential packet losses. In this paper, we propose robust FIR filters for low-frequen…
Transfer entropy can to a certain degree assess the direction in addition to the strength of the couplings within dynamic time series. The greater the transfer entropy, the greater the strength of the dependency between time series. In this work, we are interested in quantifying the effect that a gi…
This paper considers speech enhancement of signals picked up in one noisy environment which must be presented to a listener in another noisy environment. Recently, it has been shown that an optimal solution to this problem requires the consideration of the noise sources in both environments jointly.…
One of the challenges with the implementation of multi-microphone noise reduction systems in practical applications lies in the need for the knowledge of the speech and noise covariance matrices. Recently, a method based on Maximum Likelihood (ML) estimation addressed this problem. Despite its relat…