Prof. Dr. Volker Hohmann
Coordinator of CRC 1330

Management & Office


This project is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project-ID 352015383 – SFB 1330.

Section C - Applications

Section C - Applications

In section C exemplary applications are explored:

Project C1 - MIMO acoustic earpiece for combined equalization, feedback cancellation and noise reduction

The long-term goal of this project is to achieve acoustically transparent speech communication and hearing support by means of a multi-input multi-output (MIMO) earpiece with integrated microphones and receivers. The main research question is how to optimally exploit the availability of multiple microphones and receivers in the ear canal and vent to develop combined solutions for sound pressure equalization at the ear drum, for acoustic feedback cancellation, for (active) noise reduction and for occlusion control.

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Project C2 - Audio reproduction in non-optimal acoustical environments

Audio content is commonly reproduced over loudspeakers in reverberant and noisy environments. This often leads to non-optimal reproduction conditions. Impairments can both be with respect to the spatial and timbre fidelity of the reproduction as well as with respect to speech intelligibility. This project will focus on robust methods for compensating for the non-optimal acoustical conditions and hearing capabilities of the listeners that can be applied in multiple scenarios.

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Project C4 - Indication and benefit assessment of hearing devices: Which test conditions do we need?

This project aims at providing the scientific basis for the assessment of individual disability due to hearing impairment and relief obtained from hearing devices with optimum ecological validity and sufficient effect size. The measures to be developed will cover communication abilities, social interactions, and participation.

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Project C5 - Assessment of auditory function and abilities in life-like listening scenarios

Acoustic scenes created in virtual reality with life-like realism and features can be used to address important questions on auditory perception beyond the scope of the simplified stimuli and conditions of classical psychoacoustic laboratory tests.

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Project C6 - Speaker separation for hearing aids with small-footprint deep learning methods

This project explores deep learning for acoustic separation of speakers' signals captured with hearing aids. The solutions will be compatible with small-footprint hardware and should contribute to improving the communication ability of the respective user.

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(Changed: 19 Jan 2024)  | 
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