Audio-visual Virtual Reality System for Room Acoustics

We present an audio-visual Virtual Reality display system for simulated sound fields. In addition to the room acoustic simulation by means of phonon tracing and finite element method this system includes the stereoscopic visualization of simulation results using a 3D back projection system as well as auralization by use of a professional sound equipment. For auralization purposes we develop a sound field synthesis approach for accurate control of the loudspeaker system

AcMus: an open, integrated platform for room acoustics research

This article describes the design, implementation, and experiences with AcMus, an open and integrated software platform for room acoustics research, which comprises tools for measurement, analysis, and simulation of rooms for music listening and production. Through use of affordable hardware, such as laptops, consumer audio interfaces and microphones, the software allows evaluation of relevant acoustical parameters with stable and consistent results, thus providing valuable information in the diagnosis of acoustical problems, as well as the possibility of simulating modifications in the room through analytical models. The system is open-source and based on a flexible and extensible Java plug-in framework, allowing for cross-platform portability, accessibility and experimentation, thus fostering collaboration of users, developers and researchers in the field of room acoustics.CNPqFAPES

The acoustics of concentric sources and receivers – human voice and hearing applications

One of the most common ways in which we experience environments acoustically is by listening to the reflections of our own voice in a space. By listening to our own voice we adjust its characteristics to suit the task and audience. This is of particular importance in critical voice tasks such as actors or singers on a stage with no additional electroacoustic or other amplification (e.g. in ear monitors, loudspeakers, etc.). Despite the usualness of this situation, there are very few acoustic measurements aimed to quantify it and even fewer that address the problem of having a source and receiver that are very closely located. The aim of this thesis is to introduce new measurement transducers and methods that quantify correctly this situation. This is achieved by analysing the characteristics of the human as a source, a receiver and their interaction in close proximity when placed in acoustical environments. The characteristics of the human voice and human ear are analysed in this thesis in a similar manner as a loudspeaker or microphone would be analysed. This provides the basis for further analysis by making them analogous to measurement transducers. These results are then used to explore the consequences of having a source and receiver very closely located using acoustic room simulation. Different techniques for processing data using directional transducers in real rooms are introduced. The majority of the data used in this thesis was obtained in rooms used for performance. The final chapters of this thesis include details of the design and construction of a concentric directional transducer, where an array of microphones and loudspeakers occupy the same structure. Finally, sample measurements with this transducer are presented

Design and Optimisation Of Voice Alarm Systems for Underground Stations

Voice Alarm systems (VA) are an essential part of subsurface underground station emergency and evacuation systems. Their main purpose is to assist in the management of emergency situations and evacuation procedures by providing key verbal instructions to the occupants. However these life-critical systems will be ineffective if the messages broadcast are unintelligible. Unfortunately, in most London underground subsurface areas the announcements broadcast by the VA system are not adequately intelligible and often do not reach a minimum specified performance target. The performance of VA relating to its electro-acoustic characteristics is relatively complex and depends on multiple interrelated factors and operational constraints . Underground stations present complex geometrical and architectural features which severely challenge the achievement of satisfactory performance. Despite the importance of VA system, there are few works in the literature providing practical and applicable design knowledge in the context of real world underground spaces. Moreover contractual performance requirements are not suitably laid out and this can lead to ineffective designs. This research aims to provide practical design knowledge and understanding for the improvement of VA speech intelligibility performance in underground spaces. Research results were derived from measurements and designs undertaken for real scenarios. A specific knowledge base is provided on the acoustics of underground spaces, speech intelligibility and VA systems. A critical review of relevant research and performance specifications and standards is undertaken and a new performance design parameter is proposed. An empirical prediction model tool based on a large pool of measured survey data is developed for the prediction of the Speech Transmission Index of VA on platforms. A validating and comparative study is undertaken for two widely used commercial acoustic simulation programs to assess their suitability as design tools for VA systems on platforms, CATT-Acoustic and Odeon. The impact on VA performance of design variables are investigated using a computer simulation of a representative platform. A novel acoustic treatment design concept is proposed. The Yang quasi diffuse sound field theory for platforms is verified and derived knowledge expanded. Practical design recommendations are provided as well as suggestion for further work

Application of Machine Learning for the Spatial Analysis of Binaural Room Impulse Responses

Spatial impulse response analysis techniques are commonly used in the field of acoustics, as they help to characterise the interaction of sound with an enclosed environment. This paper presents a novel approach for spatial analyses of binaural impulse responses, using a binaural model fronted neural network. The proposed method uses binaural cues utilised by the human auditory system, which are mapped by the neural network to the azimuth direction of arrival classes. A cascade-correlation neural network was trained using a multi-conditional training dataset of head-related impulse responses with added noise. The neural network is tested using a set of binaural impulse responses captured using two dummy head microphones in an anechoic chamber, with a reflective boundary positioned to produce a reflection with a known direction of arrival. Results showed that the neural network was generalisable for the direct sound of the binaural room impulse responses for both dummy head microphones. However, it was found to be less accurate at predicting the direction of arrival of the reflections. The work indicates the potential of using such an algorithm for the spatial analysis of binaural impulse responses, while indicating where the method applied needs to be made more robust for more general application

Three-Dimensional Geometry Inference of Convex and Non-Convex Rooms using Spatial Room Impulse Responses

This thesis presents research focused on the problem of geometry inference for both convex- and non-convex-shaped rooms, through the analysis of spatial room impulse responses. Current geometry inference methods are only applicable to convex-shaped rooms, requiring between 6--78 discretely spaced measurement positions, and are only accurate under certain conditions, such as a first-order reflection for each boundary being identifiable across all, or some subset of, these measurements. This thesis proposes that by using compact microphone arrays capable of capturing spatiotemporal information, boundary locations, and hence room shape for both convex and non-convex cases, can be inferred, using only a sufficient number of measurement positions to ensure each boundary has a first-order reflection attributable to, and identifiable in, at least one measurement. To support this, three research areas are explored. Firstly, the accuracy of direction-of-arrival estimation for reflections in binaural room impulse responses is explored, using a state-of-the-art methodology based on binaural model fronted neural networks. This establishes whether a two-microphone array can produce accurate enough direction-of-arrival estimates for geometry inference. Secondly, a spherical microphone array based spatiotemporal decomposition workflow for analysing reflections in room impulse responses is explored. This establishes that simultaneously arriving reflections can be individually detected, relaxing constraints on measurement positions. Finally, a geometry inference method applicable to both convex and more complex non-convex shaped rooms is proposed. Therefore, this research expands the possible scenarios in which geometry inference can be successfully applied at a level of accuracy comparable to existing work, through the use of commonly used compact microphone arrays. Based on these results, future improvements to this approach are presented and discussed in detail

3D Reflector Localisation and Room Geometry Estimation using a Spherical Microphone Array

The analysis of room impulse responses to localise reflecting surfaces and estimate room ge- ometry is applicable in numerous aspects of acoustics, including source localisation, acoustic simulation, spatial audio, audio forensics, and room acoustic treatment. Geometry inference is an acoustic analysis problem where information about reflections extracted from impulse responses are used to localise reflective boundaries present in an environment, and thus estimate the geometry of the room. This problem however becomes more complex when considering non-convex rooms, as room shape can not be constrained to a subset of possible convex polygons. This paper presents a geometry inference method for localising reflective boundaries and inferring the room’s geometry for convex and non-convex room shapes. The method is tested using simulated room impulse responses for seven scenarios, and real-world room impulse responses measured in a cuboid-shaped room, using a spherical microphone array containing multiple spatially distributed channels capable of capturing both time- and direction-of-arrival. Results show that the general shape of the rooms is inferred for each case, with a higher degree of accuracy for convex shaped rooms. However, inaccuracies gen- erally arise as a result of the complexity of the room being inferred, or inaccurate estimation of time- and direction-of-arrival of reflections