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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Employing a finite number of discrete microphones, instead of a continuous distribution according to theory, reduces the physical accuracy of sound field representations captured by a spherical microphone array. For a binaural reproduction of the sound field, a number of approaches have been proposed in the literature to mitigate the perceptual impairment when the captured sound fields are reproduced binaurally. We recently presented a perceptual evaluation of a representative set of approaches in conjunction with reverberant acoustic environments. This paper presents a similar study but with acoustically dry environments with reverberation times of less than 0.25 s. We examined the Magnitude Least-Squares algorithm, the Bandwidth Extraction Algorithm for Microphone Arrays, Spherical Head Filters, spherical harmonics Tapering, and Spatial Subsampling, all up to a spherical harmonics order of 7. Although dry environments violate some of the assumptions underlying some of the approaches, we can confirm the results of our previous study: Most approaches achieve an improvement whereby the magnitude of the improvement is comparable across approaches and acoustic environments.

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