ISBN 978-3-8439-4673-5

978-3-8439-4673-5, Reihe Elektrotechnik

Ali Aroudi
Cognitive-Driven Speech Enhancement using EEG-based Auditory Attention Decoding for Hearing Aid Applications

194 Seiten, Dissertation Carl von Ossietzky Universität Oldenburg (2020), Hardcover, B5

Zusammenfassung / Abstract

Identifying the target speaker in hearing aid applications is an essential ingredient to improve speech intelligibility. Although several speech enhancement algorithms are available to reduce background noise or to perform source separation in multi-speaker scenarios, their performance depends on correctly identifying the target speaker to be enhanced. Recent advances in electroencephalography (EEG) have shown that it is possible to identify the target speaker which the listener is attending to using single-trial EEG-based auditory attention decoding (AAD) methods. However, in realistic acoustic environments the AAD performance is influenced by undesired disturbances such as interfering speakers, noise and reverberation. In addition, it is important for real-world hearing aid applications to close the AAD loop by presenting on-line auditory feedback.

This thesis deals with the problem of identifying and enhancing the target speaker in realistic acoustic environments based on decoding the auditory attention of the listener using single-trial EEG recordings. To this end, we thoroughly analyze the AAD performance in noisy and reverberant environments, we propose novel methods for decoding auditory attention and we propose open-loop and closed-loop cognitive-driven speech enhancement systems for hearing aid applications.