Gesture recognition enables a natural extension of the way we currently interact with devices. Commercially available gesture recognition systems are usually pre-trained. We propose a method that allows users to define their own gestures using only a few training examples.

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We develop a fully probabilistic approach to pure-tone audiometry. By assuming a Gaussian process based response model for test tones, the hearing threshold estimation problem becomes one of Bayesian inference. This allows the use of information-theoretic criteria to select optimal test tones.

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Hearing Aid (HA) algorithms need to be tuned (fitted) to match the impairment of each specific patient. The lack of a fundamental HA fitting theory is a strong contributing factor to an unsatisfying sound experience for about 20% of hearing aid patients. We propose here a probabilistic modeling approach to the design of HA algorithms. Our method relies on a generative probabilistic model for the hearing loss problem and provides for automated inference of the corresponding (1) signal processing algorithm, (2) the fitting solution as well as a principled (3) performance evaluation metric. All three tasks are realized as message passing algorithms in a factor graph representation of the generative model, which in principle allows for fast implementation on hearing aid or mobile device hardware. The methods are theoretically worked out and simulated with a custom-built factor graph toolbox for a specific hearing loss model.

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More Publications

How do you solve a problem that is only vaguely described? We describe here an engineering approach that guides our research on solving vaguely defined problems such as hearing impairment.

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The primary mission of the BIASlab team is to develop in-situ trainable Bayesian Intelligent Agents for applications to wearable technology.

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Bert de Vries

Professor, TU Eindhoven

Tjalling Tjalkens

Associate Professor, TU Eindhoven

Anouk van Diepen

PhD candidate, TU Eindhoven

Thijs van de Laar

PhD candidate, TU Eindhoven

Marco Cox

PhD candidate, TU Eindhoven

Ivan Bocharov

PhD candidate, TU Eindhoven

Quan (Eric) Nguyen

PhD Candidate, TU Eindhoven

Ismail Senoz

Graduate student, TU Eindhoven

Joris Kraak

Senior Software Engineer, GN Hearing

All members

We gratefully acknowledge financial support from our sponsors:

STW
GN Resound