“Parametric wave field coding for precomputed sound propagation” by Raghuvanshi and Snyder

  • ©Nikunj Raghuvanshi and John M. Snyder




    Parametric wave field coding for precomputed sound propagation

Session/Category Title: Sound & Light




    The acoustic wave field in a complex scene is a chaotic 7D function of time and the positions of source and listener, making it difficult to compress and interpolate. This hampers precomputed approaches which tabulate impulse responses (IRs) to allow immersive, real-time sound propagation in static scenes. We code the field of time-varying IRs in terms of a few perceptual parameters derived from the IR’s energy decay. The resulting parameter fields are spatially smooth and compressed using a lossless scheme similar to PNG. We show that this encoding removes two of the seven dimensions, making it possible to handle large scenes such as entire game maps within 100MB of memory. Run-time decoding is fast, taking 100μs per source. We introduce an efficient and scalable method for convolutionally rendering acoustic parameters that generates artifact-free audio even for fast motion and sudden changes in reverberance. We demonstrate convincing spatially-varying effects in complex scenes including occlusion/obstruction and reverberation, in our system integrated with Unreal Engine 3™.


    1. Ajdler, T., Sbaiz, L., and Vetterli, M. 2006. The Plenacoustic Function and Its Sampling. Signal Processing, IEEE Transactions on 54, 10 (Oct.), 3790–3804. Google ScholarDigital Library
    2. Allen, J. B., and Berkley, D. A. 1979. Image method for efficiently simulating small-room acoustics. J. Acoust. Soc. Am 65, 4, 943–950.Google ScholarCross Ref
    3. Beranek, L. L. 2003. Subjective Rank-Orderings and Acoustical Measurements for Fifty-Eight Concert Halls. Acta Acustica united with Acustica (May), 494–508.Google Scholar
    4. Bradley, J. S., and Halliwell, R. E. 1988. Accuracy and reproducibility of auditorium acoustics measures. In British Institute of Acoustics, vol. 10, 399–406.Google Scholar
    5. Calamia, P. 2009. Advances in Edge-Diffraction Modeling for Virtual-Acoustic Simulations. PhD thesis, Princeton University. Google ScholarDigital Library
    6. Chandak, A., Lauterbach, C., Taylor, M., Ren, Z., and Manocha, D. 2008. AD-Frustum: Adaptive Frustum Tracing for Interactive Sound Propagation. IEEE Transactions on Visualization and Computer Graphics 14, 6, 1707–1722. Google ScholarDigital Library
    7. Davy, J. L., Dunn, I. P., and Dubout, P. 1979. The Variance of Decay Rates in Reverberation Rooms. Acta Acustica united with Acustica (Aug.), 12–25.Google Scholar
    8. Funkhouser, T., Tsingos, N., Carlbom, I., Elko, G., Sondhi, M., West, J. E., Pingali, G., Min, P., and Ngan, A. 2004. A beam tracing method for interactive architectural acoustics. The Journal of the Acoustical Society of America 115, 2, 739–756.Google ScholarCross Ref
    9. Gade, A. 2007. Acoustics in Halls for Speech and Music. In Springer Handbook of Acoustics, T. Rossing, Ed., 2007 ed. Springer, May, ch. 9.Google ScholarCross Ref
    10. IASIG, 3D Working Group. 1999. Interactive 3D Audio Rendering Guidlelines, Level 2.0, Sept.Google Scholar
    11. ISO 3382-1:2009. Acoustics – Measurement of room acoustic parameters – Part 1: Performance spaces. International Organization for Standardization.Google Scholar
    12. James, D. L., Barbic, J., and Pai, D. K. 2006. Precomputed acoustic transfer: output-sensitive, accurate sound generation for geometrically complex vibration sources. ACM Transactions on Graphics 25, 3 (July), 987–995. Google ScholarDigital Library
    13. Kolarik, A. J., Cirstea, S., and Pardhan, S. 2011. Perceiving auditory distance using level and direct-to-reverberant ratio cues. The Journal of the Acoustical Society of America 130, 4 (Oct.), 2545.Google ScholarCross Ref
    14. Kowalczyk, K., and van Walstijn, M. 2010. Room acoustics simulation using 3-D compact explicit FDTD schemes. IEEE Transactions on Audio, Speech and Language Processing. Google ScholarDigital Library
    15. Krokstad, A. 2008. The Hundred Years Cycle in Room Acoustic Research and Design. In Reflections on sound, P. Svensson, Ed. Norwegian University of Science and Technology (NTNU), Trondheim, Norway, June, ch. 5.Google Scholar
    16. Kuttruff, H. 2000. Room Acoustics, 4 ed. Taylor & Francis.Google Scholar
    17. Laine, S., Siltanen, S., Lokki, T., and Savioja, L. 2009. Accelerated beam tracing algorithm. Applied Acoustics 70, 1 (Jan.), 172–181.Google ScholarCross Ref
    18. Mehra, R., Raghuvanshi, N., Savioja, L., Lin, M. C., and Manocha, D. 2012. An efficient GPU-based time domain solver for the acoustic wave equation. Applied Acoustics 73, 2 (Feb.), 83–94.Google ScholarCross Ref
    19. Mehra, R., Raghuvanshi, N., Antani, L., Chandak, A., Curtis, S., and Manocha, D. 2013. Wave-based Sound Propagation in Large Open Scenes Using an Equivalent Source Formulation. ACM Trans. Graph. 32, 2 (Apr.). Google ScholarDigital Library
    20. Merimaa, J., and Pulkki, V. 2005. Spatial Impulse Response Rendering I: Analysis and Synthesis. J. Audio Eng. Soc 53, 12, 1115–1127.Google Scholar
    21. Murphy, D., Kelloniemi, A., Mullen, J., and Shelley, S. 2007. Acoustic Modeling Using the Digital Waveguide Mesh. IEEE Signal Processing Magazine 24, 2 (Mar.), 55–66.Google ScholarCross Ref
    22. Raghuvanshi, N., Narain, R., and Lin, M. C. 2009. Efficient and Accurate Sound Propagation Using Adaptive Rectangular Decomposition. IEEE Transactions on Visualization and Computer Graphics 15, 5, 789–801. Google ScholarDigital Library
    23. Raghuvanshi, N., Snyder, J., Mehra, R., Lin, M. C., and Govindaraju, N. K. 2010. Precomputed Wave Simulation for Real-Time Sound Propagation of Dynamic Sources in Complex Scenes. ACM Transactions on Graphics (proceedings of SIGGRAPH 2010) 29, 3 (July). Google ScholarDigital Library
    24. Rindel, J. H., and Christensen, C. L. 2013. The use of colors, animations and auralizations in room acoustics. In Internoise 2013.Google Scholar
    25. Sabine, H. 1953. Room acoustics. Audio, Transactions of the IRE Professional Group on 1, 4, 4–12.Google ScholarCross Ref
    26. Sakamoto, S., Nagatomo, H., Ushiyama, A., and Tachibana, H. 2008. Calculation of impulse responses and acoustic parameters in a hall by the finite-difference time-domain method. Acoustical Science and Technology 29, 4.Google ScholarCross Ref
    27. Savioja, L., Rinne, T., and Takala, T. 1994. Simulation of room acoustics with a 3-D finite difference mesh. In Proceedings of the International Computer Music Conference, 463–466.Google Scholar
    28. Savioja, L. 2010. Real-Time 3D Finite-Difference Time-Domain Simulation of Mid-Frequency Room Acoustics. In 13th International Conference on Digital Audio Effects (DAFx-10).Google Scholar
    29. Schröder, D. 2011. Physically Based Real-Time Auralization of Interactive Virtual Environments. Logos Verlag, Dec.Google Scholar
    30. Siltanen, S., Lokki, T., Kiminki, S., and Savioja, L. 2007. The room acoustic rendering equation. The Journal of the Acoustical Society of America 122, 3 (Sept.), 1624–1635.Google ScholarCross Ref
    31. Siltanen, S., Lokki, T., and Savioja, L. 2009. Frequency Domain Acoustic Radiance Transfer for Real-Time Auralization. Acta Acustica united with Acustica 95, 1, 106–117.Google Scholar
    32. Siltanen, S., Lokki, T., and Savioja, L. 2010. Rays or Waves? Understanding the Strengths and Weaknesses of Computational Room Acoustics Modeling Techniques. In Proc. Int. Symposium on Room Acoustics.Google Scholar
    33. Siltanen, S., Lokki, T., and Savioja, L. 2010. Room acoustics modeling with acoustic radiance transfer. Proc. ISRA Melbourne.Google Scholar
    34. Siltanen, S. 2005. Geometry Reduction in Room Acoustics Modeling. Master’s thesis, Helsinki University of Technology.Google Scholar
    35. Southern, A., Siltanen, S., Murphy, D. T., and Savioja, L. 2013. Room Impulse Response Synthesis and Validation Using a Hybrid Acoustic Model. Audio, Speech, and Language Processing, IEEE Transactions on 21, 9, 1940–1952.Google ScholarDigital Library
    36. Stephenson, U. M., and Svensson, U. P. 2007. An improved energetic approach to diffraction based on the uncertainty principle. In 19th Int. Cong. on Acoustics (ICA).Google Scholar
    37. Stettner, A., and Greenberg, D. P. 1989. Computer Graphics Visualization for Acoustic Simulation. SIGGRAPH Comput. Graph. 23, 3 (July), 195–206. Google ScholarDigital Library
    38. Svensson, U. P., Fred, R. I., and Vanderkooy, J. 1999. An analytic secondary source model of edge diffraction impulse responses. The Journal of the Acoustical Society of America 106, 5 (Nov.), 2331–2344.Google ScholarCross Ref
    39. Takala, T., and Hahn, J. 1992. Sound rendering. SIGGRAPH Comput. Graph. 26, 2 (July), 211–220. Google ScholarDigital Library
    40. Taylor, M. T., Chandak, A., Antani, L., and Manocha, D. 2009. RESound: interactive sound rendering for dynamic virtual environments. In Proceedings of ACM conference on Multimedia, ACM, New York, NY, USA, 271–280. Google ScholarDigital Library
    41. Tsingos, N. 2009. Pre-computing geometry-based reverberation effects for games. In 35th AES Conference on Audio for Games.Google Scholar
    42. Valimaki, V., Parker, J. D., Savioja, L., Smith, J. O., and Abel, J. S. 2012. Fifty Years of Artificial Reverberation. Audio, Speech, and Language Processing, IEEE Transactions on 20, 5 (July), 1421–1448.Google Scholar
    43. Yeh, H., Mehra, R., Ren, Z., Antani, L., Manocha, D., and Lin, M. 2013. Wave-ray Coupling for Interactive Sound Propagation in Large Complex Scenes. ACM Trans. Graph. 32, 6 (Nov.). Google ScholarDigital Library

ACM Digital Library Publication:

Overview Page: