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Auralization Lauri Savioja (Tapio Lokki) Helsinki University of Technology, TKK.

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Presentation on theme: "Auralization Lauri Savioja (Tapio Lokki) Helsinki University of Technology, TKK."— Presentation transcript:

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2 Auralization Lauri Savioja (Tapio Lokki) Helsinki University of Technology, TKK

3 AGENDA, 8:45 – 9:20  Auralization, i.e., sound rendering  Impulse response  Basic principle + Marienkirche demo  Source signals and modeling of directivity of sources  Modeling from perceptual point of view  Dynamic auralization  Evaluation of auralization quality  Spatial sound reproduction  Headphones  Loudspeakers

4 Impulse response of a room 10 meters 7 meters

5 Impulse response of a room

6  A linear time-invariant system (LTI) can be modeled with an impulse response  The output y(t) is the convolution of the input x(t) and the impulse response h(t)  Discrete form (convolution is sum) Impulse response

7 Measured (binaural) impulse response of Tapiola concert hall

8 Two goals of room acoustics modeling  Goal 1: room acoustics prediction  Static source and receiver positions  No real-time requirement  Goal 2: auralization, sound rendering  Possibly moving source(s) and listener, even geometry  Both off-line and interactive (real-time) applications  Need of anechoic stimulus signals (Binaural rendering, Lokki, 2002)

9 Goal 2: Auralization / sound rendering -“Auralization is the process of rendering audible, by physical or mathematical modeling, the sound field of a source in a space, in such a way as to simulate the binaural listening experience at a given position in the modeled space.” (Kleiner et al. 1993, JAES) -Sound rendering: plausible 3-D sound, e.g., in games 3-D model  spatial IR * dry signal = auralization

10 Auralization  Goal: Plausible 3-D sound, authentic auralization  The most intuitive way to study room acoustic prediction results  Not only for experts  Anechoic stimulus signal  Reproduction with binaural or multichannel techniques  Impulse response has to contain also spatial information

11 Auralization, input  Input data:  Anechoic stimulus signal(s) !  Geometry + material data  source(s) and receiver(s) locations and orientations

12 Auralization, modeling  Source(s): omnidirectional, sometimes directional  Medium:  physically-based sound propagation in a room  perceptual models, i.e., artificial reverb  Receiver: spatial sound reproduction (binaural or multichannel)

13 Marienkirche, concert hall in Neubrandenburg (Germany)

14 source – medium – receiver (Savioja et al. 1999, Väänänen 2003)

15  Stimulus  Sound signal synthesis  Anechoic recordings Source Modeling – stimulus signal

16  Directivity is a measure of the directional characteristic of a sound source.  Point sources omnidirectional omnidirectional frequency dependent directivity characteristics frequency dependent directivity characteristics  Line and volume sources  Database of loudspeakers http://www.clfgroup.org/ http://www.clfgroup.org/ Source Modeling - Radiation

17 Anechoic stimulus signals  In a concert hall typical sound source is an orchestra  Anechoic recordings needed  Directivity of instruments also needed  We have just completed such recordings  Demo  All recordings with 22 microphones  Recordings are publicly available for Academic purposes Contact: Tapio.Lokki@tkk.fi Contact: Tapio.Lokki@tkk.fiTapio.Lokki@tkk.fi http://auralization.tkk.fi http://auralization.tkk.fi

18 Sound field decomposition (Svensson, AES22 nd 2002) diffuse reflections handled by surface sources

19 Computation vs. human perception Computation vs. Frequency resolution Computation vs. Time resolution (Svensson & Kristiansen 2002)

20 Two approaches Perceptually-based Physically-based (Väänänen, 2003)

21 Auralization: Two approaches (1)  Perceptually-based modeling  Impulse response is not computed with a geometry A ”statistical” response is applied A ”statistical” response is applied  Psychoacoustical (subjective) parameters are applied in tuning the response e.g. reverberation time, clarity, warmness, spaciousness e.g. reverberation time, clarity, warmness, spaciousness  Applications: music production, teleconferencing, computer games...

22 Auralization: Two approaches (2)  Physically-based modeling  Sound propagation and reflections of boundaries are modeled based on physics.  Impulse response is predicted based on the geometry and its properties depend on surface materials, directivity and position of sound source(s) as well as position and orientation of the listener  Applications: prediction of acoustics, concert hall design, virtual auditory environments for games and virtual reality applications, education,...

23 Dynamic auralization (≈sound rendering)  Method 1: A grid of impulse responses is computed and convolution is performed with interpolated responses:  Applied in the CATT software (http://www.catt.se)  Method 2: ”Parametric rendering”

24 Typical Auralization System 1. Scene definition 2. Parametric presentation of sound paths 3. Auralization with parametric DSP structure

25 Auralization parameters  For the direct sound and each image source the following set of auralization parameters is provided:  Distance from the listener  Azimuth and elevation angles with respect to the listener  Source orientation with respect to the listener  Reflection data, e.g. as a set of filter coefficients which describe the material properties in reflections

26 Treatment of one image source – a DSP view  Directivity  Air absorption  Distance attenuation  Reflection filters  Listener modeling  Linear system  Commutation  Cascading (Adapted from Strauss, 1998)

27 Auralization block diagram

28 Treatment of each image source

29 Late reverberation algorithm  A special version of feedback delay network (Väänänen et al. 1997)

30 A Case Study: a Lecture Room

31 Image sources 1st order

32 Image sources up to 2nd order

33 Image sources up to 3rd order

34 Distance attenuation

35 Distance attenuation (zoomed)

36 Gain + air absorption

37 Gain + air and material absorption

38 All monaural filtering

39 All monaural filtering (zoomed)

40 Treatment of each image source

41 Only ITD for pure impulse

42 Only ITD for pure impulse (zoom)

43 ITD + minimum phase HRTF

44 Monaural filterings + ITD

45 Monaural filterings + ITD + HRTF

46 Auralization block diagram

47 Reverb

48 Image sources + reverberation

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51 Dynamic Sound Rendering  Dynamic rendering  Properties of image sources are time variant The coefficients of filters are changing all the time The coefficients of filters are changing all the time  Every single parameter has to be interpolated  In delay line pick-ups the fractional delay filters have to be used to avoid clicks and artifacts  Late reverberation is static  Update rate  latency

52 Auralization quality  What is the wanted quality?  Assesment of quality is possible only by case studies  Objectively:  Acoustical attributes  With auditory modeling  Subjectively:  Listening tests

53 A case study, lecture hall T3

54 Quality of auralization (Lokki, 2002) Stimuli: clarinet drum Results clarinet:recording auralization Results drum: recording auralization

55 Spatial auditory display Nicolas Tsingos Lauri Savioja

56 Spatial Sound Reproduction Techniques  Reproduce the correct perceived location/direction of a virtual sound source to the ears of the listener  Headphone or speaker based. Binaural stereoMultiple speakers

57 Binaural and Transaural Stereophony  Natural filtering of the ears and torso  Apply a directional filtering to the signal  Head Related Transfer Functions (HRTFs)  Headphones (binaural)  Speaker pair (transaural)

58 Head Related Transfer Functions  Modeling  Finite element techniques  Measuring  Dummy-heads  Human listener  HRTFs strongly depend on the listener  Morphological differences  Adaptation by scaling in frequency domain

59 HRTF filter design  Filters separated into two parts:  1. Inter-aural time difference (ITD)  2. Minimum-phase FIR-filter  In movements:  Linear interpolation of ITD  Bilinear interpolation for FIR

60 Implementing HRTFs  Principal component analysis  HRTF is a linear combination of eigenfilters  Allows for smooth interpolation  Allows for reducing the number of operations

61 Transaural Stereophony  Cross talk cancellation  H ll and H rr are HRTFs  H rl and H lr ?

62 Amplitude/Intensity Panning  The common “surround sound”  Apply the proper gain to every speaker to reproduce the proper perceived direction  in 2D pair of loudspeakers  in 3D loudspeaker triangle  Vector-Base Amplitude Panning (image from Ville Pulkki, TKK)

63 Ambisonics  Spherical harmonics decomposition of the pressure field at a given point  1st order spherical harmonics  Sound field can be reproduced from 4 components  1 omnidirectional and 3 orthogonal figure-of-8  Allows for manipulating the sound-field  Rotations, etc.

64 Wave Field Synthesis  Reproduce the exact wave-field in the reproduction regions  Use speakers on the boundary  Kirchoff integral theorem  Sound field valid everywhere in the room  Heavy resources  In practice limited to a planar configuration

65 Comparison Technique Setup (# chans) DSPelevationimaging Sweet spot recordi ng HRTF light (2) light (2)moderateyesv.goodn/ayes Transaural light (2+) moderateyesgoodsmall yes yes Amplitude Panning average (5+) low yes (3D array) averagemedium no no Ambisonics average (4+) moderate yes (3D array) goodsmall yes yes WFS heavy (100+) high ?v.goodn/a ?

66 Which Setup for which Environment ?  Binaural systems for desktop use  Includes stereo transaural  Multi-speaker systems for multi-user  Well suited to immersive projection-based VR systems Projection screens act as low-pass filters Projection screens act as low-pass filters Video projection constraints Video projection constraints

67 Other Issues for Immersive Environments  Overall system latency  Less than 100ms is OK  Tracking the user’s head  Update binaural/transaural filters  Correction of loudspeakers gains  Room problems  Reflective surfaces

68 Summary  Auralization  Direct convolution with full directional impulse responses Computationally too heavy in practice Computationally too heavy in practice  Parametric impulse response rendering Early reflections treated separately Early reflections treated separately Statistic late reverberation Statistic late reverberation  Spatial sound reproduction  Headphones: HRTFs  Loudspeakers: VBAP, Ambisonics, Wave Field Synthesis

69 Thank you for your attention! Contact: Lauri.Savioja@tkk.fi http://auralization.tkk.fi


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