Download Room simulation for binaural sound reproduction using measured spatiotemporal impulse responses In binaural sound reproduction systems the incorporation of room simulation is important to improve sound source localisation capabilities. Thus, the localisation error can be decreased, while equivalently an enhanced externality (out of head localisation) is achieved. Previously proposed works are based on simple geometrical approaches for room simulation. In this paper an alternative method using measured room impulse responses (RIRs) is presented. Therefore, it is possible to obtain a convincing acoustical image of an existing room. The RIRs are measured using a circular microphone array to capture both temporal and spatial information of the desired room.
Download A library for realtime 3D binaural sound reproduction in pure data(PD) This paper presents a library for programming 3D binaural sound reproduction systems using Pure Data (pd), an open source computer music programming language. The theory that forms the basis of the proposed library is an improved virtual Ambisonics approach. Using this approach provides computationally efficient implementation of multiple moving sound sources, room simulation, head tracking and time varying listener positions in virtual space. Furthermore, simple GUI objects for controlling parameters are implemented to provide easy to use environment.
Download Hybrid Reverberation Processor with Perceptual Control This paper presents a hybrid reverberation processor, i.e. a realtime audio signal processing unit that combines a convolution reverb for recreating the early reflections of a measured impulse response (IR) with a feedback delay network (FDN) for synthesizing the reverberation tail. The FDN is automatically adjusted so as to match the energy decay profile of the measured IR. Particular attention is given to the transition between the convolution section and the FDN in order to avoid audible artifacts. The proposed reverberation processor offers both computational efficiency and flexible perceptual control over the reverberation effect.
Download EVERTims: Open Source Framework for Real-time Auralization in Architectural Acoustics and Virtual Reality This paper presents recent developments of the EVERTims project, an auralization framework for virtual acoustics and real-time room acoustic simulation. The EVERTims framework relies on three independent components: a scene graph editor, a room acoustic modeler, and a spatial audio renderer for auralization. The framework was first published and detailed in [1, 2]. Recent developments presented here concern the complete re-design of the scene graph editor unit, and the C++ implementation of a new spatial renderer based on the JUCE framework. EVERTims now functions as a Blender add-on to support real-time auralization of any 3D room model, both for its creation in Blender and its exploration in the Blender Game Engine. The EVERTims framework is published as open source software: http://evertims.ircam. fr.
Download Parametric Resynthesis of Measured Spatial Room Impulse Responses Spatial Room Impulse Responses (SRIRs) are fundamental to immersive audio rendering and have become a key focus of recent machine learning research in acoustics and auralization. Due to the high computational cost of direct convolution, spatial audio systems commonly employ artificial reverberation algorithms. However, these approaches often fail to accurately reproduce the spatial, temporal, and spectral characteristics of early reflections, leading to notable deviations from measured SRIRs. This paper presents a comprehensive framework for the analysis and efficient resynthesis of SRIRs captured with Spherical Microphone Arrays (SMAs). The proposed method accounts for hardware-induced artifacts, including scattering and spatial aliasing. Early reflections are reconstructed using a parametric approach based on the Herglotz analysis method, while late reverberation is synthesized using a Directional Feedback Delay Network (DFDN) with optimized filter-attenuation and correlation-matching. The proposed framework produces signals whose spatial correlation and Energy Decay Relief (EDR) closely match those of measured SRIRs, demonstrating its effectiveness for both real-time spatial audio rendering and realistic dataset generation for machine learning applications.