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The auralization of acoustic environments over headphones is often realized with data-based dynamic binaural synthesis. The required binaural room impulse responses (BRIRs) for the convolution process can be acquired by performing measurements with an artificial head for different head orientations and positions. This procedure is rather costly and therefore not always feasible in practice. Because a plausible representation is sufficient for many practical applications, a simpler approach is of interest. In this paper we present the BinRIR (Binauralization of omnidirectional room impulse responses) algorithm, which synthesizes BRIR datasets for dynamic auralization based on a single measured omnidirectional room impulse response (RIR). Direct sound, early reflections, and diffuse reverberation are extracted from the omnidirectional RIR and are separately spatialized. Spatial information is added according to assumptions about the room geometry and on typical properties of diffuse reverberation. The early part of the RIR is described by a parametric model and can easily be modified and adapted. Thus the approach can even be enhanced by considering modifications of the listener position. The late reverberation part is synthesized using binaural noise, which is adapted to the energy decay curve of the measured RIR. In order to examine differences between measured and synthesized BRIRs, we performed a technical evaluation for two rooms. Measured BRIRs are compared to synthesized BRIRs and thus we analyzed the inaccuracies of the proposed algorithm.

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