Arezoo Talebzadeh – arezoo.talebzadeh@UGent.be Ph.D. Student Ghent University Tech Lane Ghent Science Park, 126, B-9052 Gent, Belgium
Popular version of 4pNS2 – Use of virtual reality in designing and developing soundscape for dementia care facilities Presented in the afternoon of May 26, 2022 182nd ASA Meeting in Denver, Colorado Click here to read the abstract
Sound is essential in making people aware of their environment; sound also helps in recognizing the time of the day. People with dementia have difficulties understanding and identifying their senses. The sonic environment can help them navigate through the space and realize the time; it can also reduce their agitation and anxiety. Care facilities and nursing homes, and long-term cares (LTC) usually have an unfamiliar acoustic environment for anyone new in the place. A well-designed soundscape can enhance the feeling of safety, elevate the mood and enrich the atmosphere. Designing the soundscape that fosters well-being for a person with dementia is challenging as mental disorders change one’s perception of space. Soundscape is the sonic environment as perceived by a person in context.
This research aims to enhance the soundscape experience during the design and development of care facilities by using Virtual Reality and defining the context during the process.
Walking through the space while hearing the soundscape demonstrates how sound helps spatial orientation and understanding of time. Specific rooms can have a unique sound dedicated to them to help residents find the location. Natural soundscape in the lounge or sounds of coffee brewing in the dining room during breakfast. Birds sound inside residents’ rooms during the morning to elevate their mood and help them start their day.
Sound is not visual (tangible); therefore, it is hard to examine and experience the design before implementation. Virtual Reality is a suitable tool for demonstrating sound augmentation and the outcome. By walking through the space and listening to the augmented sonic environment, caregivers and family members can participate during the design process as they are most familiar with the person with dementia and their interests. This method helps in evaluating the soundscape. People with dementia have a different mental model. Virtual Reality can help feature diverse mental models and sympathize with people with dementia.
Joseph Esce – esce@hartford.edu Eoin A King – eoking@hartford.edu Acoustics Program and Lab Department of Mechanical Engineering University of Hartford 200 Bloomfield Avenue West Hartford CT 06119 U.S.A
Popular version of paper 5pSP6: “Assessing the Accuracy of Head Related Transfer Functions in a Virtual Reality Environment”, presented Friday afternoon, November 9, 2018, 2:30 – 2:45pm, RATTENBURY A/B, ASA 176th Meeting/2018 Acoustics Week in Canada, Victoria, Canada.
Introduction While visual graphics in Virtual Reality (VR) systems are very well developed, the manner in which acoustic environments and sounds may be recreated in a VR system is not. Currently, the standard procedure to represent sound in a virtual environment is to use a generic head related transfer function (HRTF), i.e. a user selects a generic HRTF from a library, with limited personal information. It is essentially a ‘best-guess’ representation of an individual’s perception of a sound source. This limits the accuracy of the representation of the acoustic environment, as every person has a HRTF that is unique to themselves.
What is a HRTF? If you close your eyes and someone jangles keys behind your head, you will be able to identify the general location of the keys just from the sound you hear. A HRTF is a mathematical function that captures these transformations, and can be used to recreate the sound of those keys in a pair of headphones – so that it appears that the sound recording of the keys has a direction associated with it. However, everyone has vastly different ear and head shapes, therefore HRTFs are unique to each person. The objective of our work was to determine how the accuracy of sound localization in a VR world varies for different users, and how we can improve it.
Test procedure In our tests, volunteers entered a VR world, which was essentially an empty room, and an invisible sound source made a short bursts of noise at various positions in the room. Volunteers were asked to point to the location of the sound source, and results were captured using the VR’s motion tracking system. Results were captured to the nearest millimeter. We tested three cases: 1) where volunteers were not allowed to move their head to assist in the localization, 2) where some slight head movements were allowed to assist in sound localization, and 3) where volunteers could turn around freely and ‘search’ (with their ears) for the sound source. The head movement was tracked by using the VR system to track the volunteer’s eye movement, and if the volunteer moved, the sound source was switched off.
Results We observed that the accuracy with which volunteers were able to localize the sound source varied significantly from person to person. There was significant error when volunteers’ head movements were restricted, but the accuracy significantly improved when people were able to move around and listen to the sound source. This suggests that the initial impression of a sounds location in a VR world is refined when the user can move their head to refine their search.
Future Work We are currently analyzing our results in more detail to account for the different characteristics of each user (e.g. head size, size and shape of ear, etc). Further, we are aiming to develop the experimental methodology to use machine learning algorithms enabling each user to create a pseudo-personalized HRTF, which would improve the immersive experience for all VR users.
Zamir Ben-Hur – zami@post.bgu.ac.il Boaz Rafaely – br@bgu.ac.il Department of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel.
David Lou Alon – davidalon@fb.com Ravish Mehra – ravish.mehra@oculus.com Oculus & Facebook, 1 Hacker Way, Menlo Park, CA 94025, USA.
Popular version of paper 3aAA10, “Localization and externalization in binaural reproduction with sparse HRTF measurement grids”. Presented Wednesday morning, May 9, 2018, 11:40-11:55 AM, 175th ASA Meeting, Minneapolis.
High-quality spatial sound reproduction is important for many applications of virtual and augmented reality. Spatial audio gives the listener the sensation that sound arrives from the surrounding 3D space, leading to immersive virtual soundscapes. To create such a virtual sound scene with headphone listening, binaural reproduction technique is being used. A key component in binaural reproduction is the head-related transfer function (HRTF). An HRTF is a mathematical representation that describes how a listener’s head, ears, and torso affect the acoustic path originating from sound source’s direction into the ear canal [1]. HRTF set is typically measured for an individual in an anechoic chamber using an HRTF measurement system. Alternatively, a generic HRTF set is measured using a manikin. To achieve a realistic spatial audio experience, in terms of sound localization and externalization, high resolution personalized HRTF (P-HRTF) is necessary. Localization refers to the ability of presenting a sound at accurate locations in the 3D space. Externalization is the ability to perceive the virtual sound as coming from outside of the head, like real world environments.
Typical P-HRTF set is composed of several hundreds to thousands of source directions measured around a listener, using a procedure which requires expensive and specialized equipment and can take a long time to complete. This motivates the development of methods that require fewer spatial samples but still allow accurate reconstruction of the P-HRTF sets with high spatial resolution. Given only sparsely measured P-HRTF, it will be necessary to reconstruct directions that were not measured, which introduces interpolation error that may lead to poor spatial audio reproduction [2]. It is therefore important to better understand this interpolation error and its effect on spatial perception. If the error is too significant then a generic HRTF may be the preferred option over a sparse P-HRTF. Figure 1 presents an illustration of the question being answered in this study.
Figure 1. Illustration of the challenge of this paper.
Prior studies suggested to represent the HRTF in the spherical-harmonics (SH) domain. Using SH decomposition, it is possible to reconstruct high resolution P-HRTF from a low number of measurements [3,4]. When using SH representation, the reconstruction error can be caused by spatial aliasing and/or of SH series truncation [4,5,6]. Aliasing refer to loss of ability to represent high frequencies due to limited number of measurements. Truncation error refer to the order limit imposed on the SH representation which further limits the spatial resolution. With small number of measurements, both errors contribute to the overall reconstruction error.
In this study, the effect of sparse measurement grids on the reproduced binaural signal is perceptually evaluated through virtual localization and externalization tests under varying conditions.
Six adult subjects participated in the experiment. The experiment was performed with the Oculus Rift headset with a pair of floating earphones (see Fig. 2). These floating earphones enabled per-user headphone equalization for the study. A stimulus of 10 second band-passed filtered white noise (0.5-15 kHz) was played-back using real-time binaural reproduction system. The system allows reproduction of a virtual sound source in a given direction, using a specific HRTF set that was chosen according to the test condition. At each trial, the sound was played from a different direction, and the subject was instructed to point to this direction using a virtual laser pointer controlled by the subject’s head movement. Next, the participant was asked to report whether the stimulus was externalized or internalized.
Figure 2. The experiment setup, including a Rift headset and floating earphones.
We analyzed the localization results by means of angular errors. The angular errors were calculated as the difference between the perceptually localized position and the true target position. Figure 3 depicts the mean sound localization performance for different test conditions (Q, N), where Q is the number of measurements and N is the SH order. The figure shows averaged error across all directions (upper plot) and errors in azimuth and elevation (lower plots) separately. The externalization results were analyzed as average percentage of responses that the subjects marked as being externalized. Figure 4 shows the externalization results averaged across all directions and subjects.
The results demonstrate that high number of measurements leads to better localization and externalization performances, where most of the effect is in the elevation angles. Compared to the performance of a generic HRTF, P-HRTF with 121 measurements and SH order 10 achieves similar results. The results suggest that for achieving improved localization and externalization performance compare to a generic HRTF, at least 169 directional measurements are required.
Figure 3. Localization results of angular error (in degrees) for different conditions of (Q,N), where Q is the number of measurements and N is the SH order. Upper plot show the overall angular error, and lower plots show separate errors for azimuth and elevation.
Figure 4. Results of externalization performance.
References
[1] J. Blauert, “Spatial hearing: the psychophysics of human sound localization”. MIT press, 1997.
[2] P. Runkle, M. Blommer, and G. Wakefield, “A comparison of head related transfer function interpolation methods,” in Applications of Signal Processing to Audio and Acoustics, 1995., IEEE ASSP Workshop on. IEEE, 1995, pp. 88–91.
[3] M.J.Evans,J.A.Angus,andA.I.Tew,“Analyzing head-related transfer function measurements using surface spherical harmonics,” The Journal of the Acoustical Society of America, vol. 104, no. 4, pp. 2400–2411, 1998.
[4] G. D. Romigh, D. S. Brungart, R. M. Stern, and B. D. Simpson, “Efficient real spherical harmonic representation of head-related transfer functions,” IEEE Journal of Selected Topics in Signal Processing, vol. 9, no. 5, pp. 921–930, 2015.
[5] B. Rafaely, B. Weiss, and E. Bachmat, “Spatial aliasing in spherical microphone arrays,” IEEE Transactions on Signal Processing, vol. 55, no. 3, pp. 1003–1010, 2007.
[6] A. Avni, J. Ahrens, M. Geier, S. Spors, H. Wierstorf, and B. Rafaely, “Spatial perception of sound fields recorded by spherical microphone arrays with varying spatial resolution,” The Journal of the Acoustical Society of America, vol. 133, no. 5, pp. 2711–2721, 2013.
W.M. To – wmto@ipm.edu.mo Macao Polytechnic Institute, Macao SAR, China. A. Chung – ac@smartcitymakter.com Smart City Maker, Denmark. B. Schulte-Fortkamp – b.schulte-fortkamp@tu-berlin.de Technische Universität Berlin, Berlin, Germany.
Popular version of paper 2aNS, “How virtual reality technologies can enable better soundscape design” Presented Tuesday morning, November 29, 2016 172nd ASA Meeting, Honolulu
The quality of life including good sound quality has been sought by community members as part of the smart city initiative. While many governments have placed special attention to waste management, air and water pollution, acoustic environment in cities has been directed toward the control of noise, in particular, transportation noise. Governments that care about the tranquility in cities rely primarily on setting the so-called acceptable noise levels i.e. just quantities for compliance and improvement [1]. Sound quality is most often ignored. Recently, the International Organization for Standardization (ISO) released the standard on soundscape [2]. However, sound quality is a subjective matter and depends heavily on the perception of humans in different contexts [3]. For example, China’s public parks are well known to be rather noisy in the morning due to the activities of boisterous amateur musicians and dancers – many of them are retirees and housewives – or “Da Ma” [4]. These activities would cause numerous complaints if they would happen in other parts of the world, but in China it is part of everyday life.
According to the ISO soundscape guideline, people can use sound walks, questionnaire surveys, and even lab tests to determine sound quality during a soundscape design process [3]. With the advance of virtual reality technologies, we believe that the current technology enables us to create an application that immerses designers and stakeholders in the community to perceive and compare changes in sound quality and to provide feedback on different soundscape designs. An app has been developed specifically for this purpose. Figure 1 shows a simulated environment in which a student or visitor arrives the school’s campus, walks through the lawn, passes a multifunctional court, and get into an open area with table tennis tables. She or he can experience different ambient sounds and can click an object to increase or decrease the volume of sound from that object. After hearing sounds at different locations from different sources, the person can evaluate the level of acoustic comfort at each location and express their feelings toward overall soundscape. She or he can rate the sonic environment based on its degree of perceived loudness and its level of pleasantness using a 5-point scale from 1 = ‘heard nothing/not at all pleasant’ to 5 = ‘very loud/pleasant’. Besides, she or he shall describe the acoustic environment and soundscape using free words because of the multi-dimensional nature of sonic environment.
Figure 1. A simulated soundwalk in a school campus.
To, W. M., Mak, C. M., and Chung, W. L.. Are the noise levels acceptable in a built environment like Hong Kong? Noise and Health, 2015. 17(79): 429-439.
ISO. ISO 12913-1:2014 Acoustics – Soundscape – Part 1: Definition and Conceptual Framework, Geneva: International Organization for Standardization, 2014.
Kang, J. and Schulte-Fortkamp, B. (Eds.). Soundscape and the Built Environment, CRC Press, 2016.