Binaural reproduction can be used in listening experiments under real-life conditions to achieve a high realism and good reproducibility. In recent years a clear trend to more individual reproduction can be observed as the ability to measure individual head-related-transfer-functions (HRTFs) is becoming more widespread. The question of the accuracy and reproduction methods needed for a realistic playback however has not been sufficiently answered. To evaluate an appropriate approach for binaural reproduction via headphones different head-related-transfer-functions (HRTFs) and reproduction methods were compared in this paper. In a listening test eleven explicitly trained participants were asked to localize eleven sound sources positioned in the right hemisphere using the proximal pointing method. Binaural stimuli based on individually measured HRTFs were compared to those of an artificial head in a static reproduction of stimuli and in three dynamic reproduction methods of different resolutions (5 • , 2.5 • and 1 • ). Unsigned errors in azimuth and elevation as well as front-back-confusions and in-head-localization were observed. Dynamic reproduction of any resolution applied turned out fundamental for a reduction of undesired front-back-confusions and in-head-localization. Individually measured HRTFs showed a smaller effect on localization accuracy compared to the influence of dynamic sound reproduction. They were mainly observed to reduce the front-back-confusion rate.

While binaural technology applications gained in popularity in recent years, the majority of applications still use non-individual Head-Related Transfer Functions (HRTFs) from artificial heads. These datasets enable a reasonably good spatial localization which works especially well when using an additional visual cue. However, certain applications, for example research of spatial hearing or hearing attention, require an physically exact and realistic binaural signal. Moreover, it was shown in many experiments that there is a substantial gain from the use of individual HRTFs, for example in localization tasks. The limiting factor that prohibits the widespread use of individual HRTFs is the acquisition of such data. A substantial hardware requirement obstructs a more universal usage. Even for institutions that allow individual measurements, the measurement time that is required, and that the subjects are required to remain motionless made most measurements unfeasible in the past. This time requirement has recently been reduced by the use of parallelization in the measurement signal which lead to the development of fast measurement systems capable of acquiring individual and spatially dense HRTF. This thesis provides a objective and subjective evaluation of such a system that is designed with the goal of little disturbance of the measurements in mind. The construction is detailed, followed by both an objective and subjective evaluation. A detailed investigation into additional distortion of the sound field introduced by the system itself is presented and it is shown that the system performs comparably to a conventional system in terms of sound source localization. Furthermore, a method is introduced and evaluated to further reduce the measurement time by using continuous rotation during the measurement. This method is used to reduced the measurement duration from eight minutes to three minutes without audible differences. The introduced methods are also used to reducing additional errors from subject movement. It is shown that this movement can be reduced by a visual feedback system to a level that can be compensated efficiently. und sechs Jahre lang eine gute Büro-Nachbarin und Freundin war. Außerdem danke ich für viel Unterstützung in meinen ersten Jahren Dr.-Ing. Martin Pollow, Dr.-Ing. Markus Müller-Trapet und Dr.-Ing. Martin Guski. Für immer unterhaltsame, dringend benötigte Kaffeepausen und gute Zusammenarbeit danke ich außerdem Michael Kohnen, Jens Mecking, Phillip Schäfer und Hark Braren. Etliche Versuche, welche in dieser Arbeit vorgestellt werden, wurden von Studenten durchgeführt und ausgewertet. Für ihren Einsatz danke ich Angela Friedrich, Dorothea Setzer, Shaima'a Doma und Saskia Wepner. Letztlich geht mein Dank an meine Freunde und Familie. Meine Eltern, Großeltern und Geschwister haben mich zu dem gemacht, der ich heute bin, und ich bin sehr dankbar für die anhaltende Unterstützung bei allem, was ich mache. Meinem guten Freund Christian Rohlfing danke ich für die lange Freundschaft, die uns schon sei...

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