Paper-Conference

K-shot learning of acoustic context

In order to personalize the behavior of hearing aid devices in different acoustic scenes, we need personalized acoustic scene …

Ivan Bocharov, Bert de Vries, Tjalling Tjalkens

A parametric approach to Bayesian optimization with pairwise comparisons

Optimizing a (preference) function through a small number of pairwise comparisons is challenging since pairwise comparisons provide …

Marco Cox, Bert de Vries

Variational Stabilized Linear Forgetting in State-Space Models

State-space modeling of non-stationary natural signals is a notoriously difficult task. As a result of context switches, the memory …

Thijs van de Laar, Marco Cox, Anouk, Bert de Vries

A probabilistic modeling approach to hearing loss compensation

Hearing loss is a serious and prevalent condition that is characterized by a frequency-dependent loss of sensitivity for acoustic …

Thijs van de Laar, Bert de Vries

A Gaussian process mixture prior for hearing loss modeling

Machine learning approaches to hearing loss estimation can significantly reduce the number of required experiments, but require a good …

Marco Cox, Bert de Vries

An In-situ Trainable Gesture Classifier

Gesture recognition, i.e., the recognition of pre-defined gestures by arm or hand movements, enables a natural extension of the way we …

Anouk Van Diepen, Marco Cox, Bert de Vries

Probabilistic Inference-based Reinforcement Learning

We introduce probabilistic inference-based reinforcement learning (PIReL), an approach to solve decision making problems by treating …

Eric Nguyen, Bert de Vries, Tjalling Tjalkens

A Probabilistic Approach To Hearing Loss Compensation

Modern hearing aids use Dynamic Range Compression (DRC) as the primary solution to combat Hearing Loss (HL). Unfortunately, common DRC …

Mojtaba Farmani, Bert de Vries