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Motion Simulation in the Environment for Auditory Research. Braxton B. Boren, Mark Ericson Nov. 1, 2011. Introduction. ARL’s Environment for Auditory Research (EAR) contains state-of-the-art facilities for auditory simulations

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Motion simulation in the environment for auditory research l.jpg

Motion Simulation in the Environment for Auditory Research

Braxton B. Boren, Mark Ericson

Nov. 1, 2011


Introduction l.jpg
Introduction

  • ARL’s Environment for Auditory Research (EAR) contains state-of-the-art facilities for auditory simulations

  • Realistic auditory environments should contain both static and moving sources

  • Moving sources are much more difficult to simulate in a 57-channel audio system

    • Multichannel audio editors

    • Max/MSP

    • Matlab

  • Using streaming audio buffers, the EAR’s Sphere Room has been equipped to simulate moving sources by automatically generating source paths and processing each source’s motion in real time.


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ENVIRONMENT FOR AUDITORY RESEARCH

Sphere Room

  • The Sphere Room is a 140 m3 (5.3m × 5.4m × 4.9m) auditory virtual reality space designed to facilitate investigations of:

    • -Integrity of auditory virtual spaces

    • -Realism of complex auditory simulations

    • -Effects of changes in Head-Related TransferFunctions on auditory perception

    • -Effect of helmets and other headgear on spatial orientation

The room contains 57 loudspeakers separated vertically by 30°, constituting a sphere surrounding the listener. This configuration of loudspeakers enables virtual sound source movement and sound projection in an almost 360° sphere.

Unlimited stationary or moving sound sources may be presented to any combination of the 57 loudspeakers permitting generation of realistic and dynamically changing acoustic environments


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Streaming Audio in Matlab

  • PortAudio API: allows low-level control of multichannel audio devices through the Matlab programming environment

    • - Low system latency

    • - High audio fidelity

  • Streaming Audio: short buffers update every 11.5 milliseconds with new audio data

    • - Loudspeaker gains are pre-calculated

    • - Signal processing can be enacted in real time

  • Static sources can be placed in background at specific positions

  • Additional moving sources can be added in a single virtual environment


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Source Motion Paths

  • Virtual source motion paths are defined parametrically, over time

    • - Circular

    • - Elliptical

    • - ‘Dogbone’


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Panning Algorithms

  • Distance-Based Amplitude Panning (DBAP), Lossius et al., 2009

    • loudspeaker gains are determined by each speaker’s distance from virtual audio source

    • independent of listener position

    • provides smooth motion panning for virtual sources located on loudspeaker array

    • cannot simulate sources outside array


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Panning Algorithms

  • Vector Base Amplitude Panning (VBAP), Pulkki, 1997

    • Defines each loudspeaker as a position vector

    • Given a set of three linearly independent speaker vectors, VBAP can simulate a source within the speaker triangle as a linear combination of the three vectors

    • The coefficient of each vector is the gain of the corresponding speaker


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Panning Algorithms

  • Vector Base Amplitude Panning (VBAP), Pulkki, 1997

    • VBAP is more robust than DBAP given a fixed listener position

    • Allows efficient simulation of virtual sources outside the loudspeaker array

    • Requires an algorithm for detecting vector/triangle intersections


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Assigning triangles to sources

  • Parametrically define the triangle’s plane:

  • If a given ray intersects the plane, find its parametric coordinates s and t

  • If (s + t) is between 0 and 1, the ray intersects the triangle

Ray-Triangle Intersection,

Sunday, 2003


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Assigning triangles to sources

Ray-Triangle Intersection,

Sunday, 2003

  • Requires 5 distinct dot product operations

  • Not as efficient as other algorithms for dynamic environments

  • But it’s more efficient for static sets of triangles because the planes’ normal vectors can be pre-computed


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Signal Processing

  • High-quality vehicular recordings are available with included x-y-z coordinates

    • These already contain attenuation, air absorption, and Doppler shift

    • Position data can be read and interpolated to determine pan positions

  • To allow arbitrary movement of any signal, signal processing is added

    • Attenuation and air absorption coefficients are pre-computed

    • Signal gain and one-pole filter are updated in real time before loading the streaming audio buffer

    • Doppler shift is more computationally expensive

      • Matlab isn’t fast enough to do it in real time

      • May later be implemented from C++

  • Need better constant recordings of vehicular motion

    • Current recordings of vehicles idling are unconvincing

    • Not as important for slower sources that don’t change with velocity


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Discussion

  • With a full signal processing load, this system can process up to four independent moving sources at once

  • Pre-calculations can take longer if different sources’ velocities and path lengths have very high least-common multiples

  • Static sources can be added in specific channels to add background ambience


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Conclusions

  • Real time streaming audio allows simulated motion of any parametric path

  • Two different panning algorithms have been implemented

    • DBAP is simpler and better for listener-independent reproduction

    • VBAP is more robust and better for a fixed listener position

  • Attenuation and air absorption filtering can be applied in real time to give more realistic distance cues

  • This system will be used in a series of auditory simulations and experiments ongoing at EAR


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References

  • Henry, P., Amrein, B., & Ericson, M., “The Environment for Auditory Research”, Acoustics Today, 5(3), 2009.

  • Kleiner M., Brainard D., & Pelli D., “What's new in Psychtoolbox-3?”, Perception 36 ECVP Abstract Supplement, 2007.

  • Lossius, T. Baltazar, P, & de la Hogue, T., “DBAP - Distance-Based Amplitude Panning”, Proceedings of the2009 International Computer Music Conference,2009.

  • Pulkki, V., “Virtual Sound Source Positioning Using Vector Base Amplitude Panning”, J. Audio Eng. Soc., 45, 1997.

  • Sunday, D., “Intersections of Rays, Segments, Planes and Triangles in 3D”, 2003.


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