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Bachelor-Vortrag: Model-Based Algorithms for Retrospective Individualization of Binaural Signals

Frederick Pietschmann
Freitag, 8. Oktober 2021
10:00 Uhr
virtueller Konferenzraum

With binaural signals, it is possible to capture the sensation of spatial hearing that humans are used to from real-life auditory scenes. However, because binaural recordings are always individualized for a specific target person, the authenticity of a binaural recording is perceived differently by different listeners. It is therefore desirable that a binaural recording is always individualized for the respective listener.

In this thesis, the existing Binaural Cue Adaptation (BCA) system from the Institute of Communication Systems is adjusted and reinterpreted for it to be able to retrospectively individualize an existing binaural signal for a new target person. Existing approaches to the main components of the BCA system, the Localization block and the Modification block, are reviewed and analyzed and multiple new concepts and ideas are introduced and algebraically described: New optimization target functions, a concept for joint optimization over multiple frequencies and multiple approaches that attempt to lessen the impact of artifacts which may occur due to model mismatches and / or erroneous location estimates.

A theoretical evaluation is conducted in which the localization performance of both existing and new approaches is benchmarked. The results confirm that some of the newly proposed ideas and concepts improve the overall performance of the BCA system.