Samuel Siltanen

The room acoustic rendering equation

An integral equation generalizing a variety of known geometrical room acoustics modeling algorithms is presented. The formulation of the room acoustic rendering equation is adopted from computer graphics. Based on the room acoustic rendering equation, an acoustic radiance transfer method, which can handle both diffuse and nondiffuse reflections, is derived. In a case study, the method is used to predict several acoustic parameters of a room model. The results are compared to measured data of the actual room and to the results given by other acoustics prediction software. It is concluded that the method can predict most acoustic parameters reliably and provides results as accurate as current commercial room acoustic prediction software. Although the presented acoustic radiance transfer method relies on geometrical acoustics, it can be extended to model diffraction and transmission through materials in future.

Engaging concert hall acoustics is made up of temporal envelope preserving reflections

Strong, exciting, and engaging sound is perceived in the best concert halls. Here, it is shown that wideband early reflections that preserve the temporal envelope of sound contribute to the clear and open acoustics with strong bass. Such reflections are fused with the direct sound due to the precedence effect. In contrast, reflections that distort the temporal envelope render the sound weak and muddy because they partially break down the precedence. The presented findings are based on the earlier psychoacoustics research, and confirmed by a perceptual evaluation with six simulated concert halls that have same monaural room acoustical parameter values according to ISO3382-1.

Geometry reduction in room acoustics modeling

The complexity of a room model affects to the computational resources required to model its acoustics by means of geometrical acoustics modeling methods. Thus, a method for reducing the geometry of the room models is presented for static room geometries. The topology of the model is simplified in a process where the model is first decomposed into a volumetric structure. The surface is reconstructed by utilizing this structure, and subsequently simplified by merging coplanar regions. The results of the method are verified by extracting room acoustical attributes from the original and reduced models with the ODEON room acoustics prediction software. It is shown that the most important acoustic properties have been preserved, even with relatively high reduction rates.

Frequency domain acoustic radiance transfer for real-time auralization

A method for modeling room acoustics and auralizing the results in real time with a moving listener is presented. The acoustics modeling is based on the acoustic radiance transfer technique which is capable of modeling arbitrary reflection properties of different materials. The novel idea of implementing this technique in frequency domain allows modeling of all frequencies at once as the time domain technique requires separate runs for each frequency band. Since the auralization of the results requires scaling, adding, and delaying responses as well as convolving them with head-related impulse responses, the massive parallel computation capacity of modern graphics hardware is utilized. Thus, realistic interactive walkthroughs are possible in typical room models with a stationary source.

Room Impulse Response Synthesis and Validation Using a Hybrid Acoustic Model

Synthesizing the room impulse response (RIR) of an arbitrary enclosure may be performed using a number of alternative acoustic modeling methods, each with their own particular advantages and limitations. This article is concerned with obtaining a hybrid RIR derived from both wave and geometric-acoustics based methods, optimized for use across different regions of time or frequency. Consideration is given to how such RIRs can be matched across modeling domains in terms of both amplitude and boundary behavior and the approach is verified using a number of standardised case studies.

Modeling incoherent reflections from rough room surfaces with image sources

Reflections at rough surfaces change the temporal structure of the reflected signal. This paper shows how to incorporate this temporal behavior in geometric room acoustics modeling. Specifically, a beam tracer is used for calculating the image sources and reflection paths. The roughness of the surfaces is taken into account in post-processing. A single reflection is assumed to distribute the energy according to an exponential function in time based on Biots rough surface modeling theory. Multiple reflections are modeled with convolutions of exponential functions which are approximated as gamma functions.

Acoustics of Epidaurus - Studies With Room Acoustics Modelling Methods

The 3D model of Epidaurus is simulated with two room acoustics modelling methods. The low frequencies up to 1000 Hz are simulated with a 3D FDTD method able to predict the wave-based phenomena such as diffraction and interference. The high frequencies are predicted with a beam tracing method. The early parts of the computed impulse responses are analyzed to explain the well-known acoustics for speech in the ancient theatres. The prediction results are compared to real measurements and visualized with various methods both in the time domain and in the frequency domain. The results suggest that when an actor was on the stage (which does not exist anymore) his direct sound was supported by several early reflections from the ground, from the stage, and from the staircases of the audience area. All this early energy is assumed to fuse well with the direct sound resulting in a strong voice being perceived at every seat in the audience.

Concert hall geometry optimization with parametric modeling tools and wave-based acoustic simulations

Advances in computational capacity made available through graphics processing unit (GPU) processing and developments in parametrically driven design tools are creating new possibilities for acoustic design and analysis. In particular, wave-based numerical simulations are becoming more tractable, and geometry manipulations, which were once cumbersome manual work, can now be automated. A case study of concert hall section profile optimization is presented. Using RHINOCEROS software with the GRASSHOPPER parametric modeling plugin, geometries were automatically generated based on a few parameters, then evaluated using Finite Difference Time Domain (FDTD) numerical simulations using GPU processing in MATLAB. The results from each iteration are used to inform a global optimization algorithm that conducts an intelligent search of the parameter space to find a solution in as few iterations as possible. The optimization is based on a stochastic model of the multidimensional objective function. The objective function is iteratively sampled and a simplified Bayesian approach is used for finding the set of parameters which is most likely to improve the current estimate of the global minimum at each iteration. With this method, curved and linear iterations of the sidewalls and under-balcony surfaces of a concert hall section were investigated. The objective was to deliver the most early energy, in the most uniform distribution, from multiple sources to multiple receiver positions.

Acoustic visualizations using surface mapping

Sound visualizations have been an integral part of room acoustics studies for more than a century. As acoustic measurement techniques and knowledge of hearing evolve, acousticians need more intuitive ways to represent increasingly complex data. Microphone array processing now allows accurate measurement of spatio-temporal acoustic properties. However, the multidimensional data can be a challenge to display coherently. This letter details a method of mapping visual representations of acoustic reflections from a receiver position to the surfaces from which the reflections originated. The resulting animations are presented as a spatial acoustic analysis tool.

Diffraction modeling in acoustic radiance transfer method

The room acoustic radiance transfer method is a solution to recently presented room acoustic rendering equation which formulates the mathematical basis for all the ray‐based (geometrical) room acoustic modeling algorithms. The basic acoustic transfer method gives as accurate results as the state‐of‐the‐art commercial room acoustic modeling software. However, the basic method still lacks, e.g., diffraction modeling and modeling of complex reflections from surfaces. In this paper we discuss different diffraction modeling methods in the light of the acoustic radiance transfer method. The problems as well as benefits of each diffraction modeling method are summarized to understand which one of them can be implemented together with acoustic radiance transfer. Finally, some implementation examples are given.