AES Europe 2025

Virtual acoustic systems can artificially alter a recording studio's reverberation in real time using spatial room impulse responses captured in different spaces. By recreating another space's acoustic perception, these systems influence various aspects of a musician's performance. Traditional methods involve recording a dry performance and adding reverb in post-production, which may not align with the musician's artistic intent. In contrast, virtual acoustic systems allow simultaneous recording of both artificial reverb and the musician's interaction using standard recording techniques—just as it would occur in the actual space. This study analyzes immersive recordings of nearly identical musical performances captured in both real concert hall and McGill University's Immersive Media Lab (Imlab), which features a new dedicated virtual acoustics software, and highlights the similarities and differences between the performances recorded in the real space and its virtual counterpart.

The acoustic behaviour of an auditorium is analysed after measurements performed according to the ISO 3382:1 standard. The all-pole analysis of the measured impulse responses confirms the hypothesis that all responses have a common component that can be attributed to room characteristis. Results from a subsequent non-parametric analysis allows conjecturing that the overall reponse of the acoustic channel between two points may de decomposed in three components: one related to source position, another related to the room, and the last one depending on the position of the receiver.

Sound fields in enclosures comprise a combination of directional and diffuse components. The directional components include the direct path from the source and the early specular reflections. The diffuse part starts with the first early reflection and builds up gradually over time. An ideal diffuse field is achieved when incoherent reflections begin to arrive randomly from all directions. More specifically, a diffuse field is characterized by having uniform energy density (i.e., independence from measurement position) and an isotropic distribution (i.e. random directions of incidence), which results in zero net energy flow (i.e. the net time-averaged intensity is zero). Despite this broad definition, real diffuse sound fields typically exhibit directional characteristics owing to the geometry and the non-uniform absorptive properties of rooms.

Several models and data-driven metrics based on the definition of a diffuse field have been proposed to assess diffuseness. A widely used metric is the _mixing time_, which indicates the transition of the sound field from directional to diffuse and is known to depend, among other factors, on the room geometry.

The concept of mixing time is closely linked to normalized echo density (NEDP), a measure first used to estimate the mixing time in actual rooms (Abel and Huang, 2006), and later to assess the quality of artificial reverberators in terms of their capacity to produce a dense reverberant tail (De Sena et al., 2015). NEDP is calculated over room impulse responses measured with a pressure probe, evaluating how much the RIR deviates from a normal distribution. Another similar temporal/statistical measure, kurtosis, has been used to similar effect (Jeong, 2016). However, neither NEDP nor kurtosis provides insights into the directional attributes of diffuse fields. While both approaches rely on statistical reasoning rather than identifying individual reflections, another temporal approach uses matching pursuit to identify individual reflections (Defrance et al., 2009).

Another set of approaches focuses on the net energy flow aspect of the diffuse field, providing an energetic analysis framework either in the time domain (Del Galdo et al., 2012) or in the time-frequency domain (Ahonen and Pulkki, 2009). These approaches rely on calculating the time-averaged active intensity, either using intensity probes or first- and higher-order Ambisonics microphones, where a pseudo-intensity-based diffuseness is computed (Götz et al., 2015). The coherence of spherical harmonic decompositions of the sound field has also been used to estimate diffuseness (Epain and Jin, 2016). Beamforming methods have likewise been applied to assess the directional properties of sound fields and to illustrate how real diffuse fields deviate from the ideal (Gover et al., 2004).

We propose a spatio-spectro-temporal (SST) sound field analysis approach based on a sparse plane-wave decomposition of sound fields captured using a higher-order Ambisonics microphone. The proposed approach has the advantage of analyzing the progression of the sound field’s diffuseness in both temporal and spatial dimensions. Several derivative metrics are introduced to assess temporal, spectro-temporal, and spatio-temporal characteristics of the diffuse field, including sparsity, diversity, and isotropy. We define the room sparsity profile (RSP), room sparsity relief (RSR), and room sparsity profile diversity (RSPD) as temporal, spectro-temporal, and spatio-temporal measures of diffuse fields, respectively. The relationship of this new approach to existing diffuseness measures is discussed and supported by experimental comparisons using 4th- and 6th-order acoustic impulse responses, demonstrating the dependence of the new derivative measures on measurement position. We conclude by considering the limitations and applicability of the proposed approach.

Ambisonic technology has recently gained popularity in room acoustic measurements due to its ability to capture both general and spatial characteristics of a sound field using a single microphone. On the other hand, conventional measurement techniques conducted in accordance with the ISO 3382-1 standard require multiple transducers, which results in more time-consuming procedure. This study presents a case study on the use of ambisonic technology to evaluate the room acoustic parameters of a medium-sized recording studio.
Two ambisonic microphones, a first-order Sennheiser Ambeo and a third-order Zylia ZM1-3E, were used to record spatial impulse responses in 30 combinations of sound source and receiver positions in the recording studio. Key acoustic parameters, including Reverberation Time (T30), Early Decay Time (EDT) and Clarity (C80), were calculated using spatial decomposition methods. The Interaural Cross-Correlation Coefficient (IACC) was derived from binaural impulse responses obtained using the MagLS binauralization method. The results were compared with conventional omnidirectional and binaural microphone measurements to assess the accuracy and advantages of ambisonic technology. The findings show that T30, EDT, C50 and IACC values measured with the use of ambisonic microphones are consistent with those obtained from conventional measurements.
This study demonstrates the effectiveness of ambisonic technology in room acoustic measurements by capturing a comprehensive set of parameters with a single microphone. Additionally, it enables the estimation of reflection vectors, offering further insights into spatial acoustics.