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Akustik-Blog

Shaima’a Doma: Development of a demonstration and evaluation tool for individualized binaural technology

17. August 2018 | von
Wann:
2018-11-09 um 11:00 – 12:00
2018-11-09T11:00:00+01:00
2018-11-09T12:00:00+01:00
Wo:
Institut für Technische Akustik
Kopernikusstraße 5
52074 Aachen
Deutschland
Preis:
Kostenlos

The transfer function from an arbitrary source position to the ear canal entrance is characterized by typical interactions with head, pinna and torso geometry. This highly individual filtering of sound is described by the head-related transfer function (HRTF) and is essential for a realistic spatial auditory reproduction.

Obtaining individual HRTFs of high quality, however, requires specialized equipment that is not widely available. In some cases, it has shown to be particularly difficult, e.g. for children, whose movement during the measurement leads to inaccurate results.

Individualized HRTFs offer a compromise by making modifications to a given non-individual HRTF set. Over the past years, various approaches have been discussed, such as individualization of the Interaural Time Difference (ITD), frequency scaling or methods based on Principal Component Analysis (PCA). These methods use anthropometric dimensions to estimate a subject’s individual HRTF. The dimensions can, for instance, be obtained from 3D images generated by structured light scanners or magnetic resonance imaging (MRI).
In this thesis, a demonstration tool is developed. With this tool, a direct auralization is possible, whilst manipulating parameters of several of the aforementioned HRTF individualization methods. Using a set of exemplary virtual acoustic scenes, the user can modify a provided HRTF set and observe the resulting differences. The tool shall find application in the subjective evaluation and optimization of HRTFs.
A listening test is further conducted, investigating just noticeable differences (JNDs) in anthropometric measures, which are used in the demonstration tool as part of the reconstruction of HRTFs from principal components. Suitable step sizes for tunable parameters in the tool are derived from the results.

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