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Signal Processing for Spatial Sound Control
Dr.-Ing. Gerald Enzner
Institut für Kommunikationsakustik (IKA)
Winter term, 2010/2011
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Outline
◮ Spatial Audio Systems
◮ Digital Signal Processing
◮ Rapid Prototyping with Matlab
◮ Course Organization
◮ Previous Student Project: HRIR Demonstrator
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 2/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Motivation of Spatial Sound Control
◮ The Dimension of Spatial Sound
• spaciousness or outdoorness (e.g., wind, backgroundnoise, roads, towns, birds, distant objects)
• indoor sound characteristics (e.g., room size,reverberation, timbre, reflections, closer objects)
• sound source properties (e.g., direction, distance, size,focus, diffuseness, directivity)
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 3/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Motivation of Spatial Sound Control
◮ The Dimension of Spatial Sound
• spaciousness or outdoorness (e.g., wind, backgroundnoise, roads, towns, birds, distant objects)
• indoor sound characteristics (e.g., room size,reverberation, timbre, reflections, closer objects)
• sound source properties (e.g., direction, distance, size,focus, diffuseness, directivity)
◮ Human Auditory System
• resolves spatial sound cues (sound characteristics)
• interacts with the acoustical environments
• performs auditory scene analysis (grouping andsegregation of sound sources)
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 3/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Spatial Sound Using Loudspeakers
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 4/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
History and Driving Forces
◮ Basic Evolution of Loudspeaker Reproduction Systems
• stereophonic sound: Ader’s experiments 1881, Blumlein’spatent 1931, consumer stereo after 1950’s (Vinyl and FM)
• multi-channel stereo (3,4,5,6-channel): first, using analogmatrix encoding, then, digital low-bit-rate encoding
• standardization: ITU-R 5.1 surround loudspeaker format
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 5/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
History and Driving Forces
◮ Basic Evolution of Loudspeaker Reproduction Systems
• stereophonic sound: Ader’s experiments 1881, Blumlein’spatent 1931, consumer stereo after 1950’s (Vinyl and FM)
• multi-channel stereo (3,4,5,6-channel): first, using analogmatrix encoding, then, digital low-bit-rate encoding
• standardization: ITU-R 5.1 surround loudspeaker format
◮ Accelerators
• moving pictures industry (music industry less successful):Dolby, Digital Theater Systems, Sony, MPEG
• storage media and audio codecs: CD, DVD, Blu-ray
• consumer electronics and related technical sound quality(i.e., SNR, dynamic range, frequency range)
• low-cost integrated circuits: DSP, ASIC, FPGA
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 5/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Ader’s Stereo Experiment
Figure 3-1: The first stereophonic transmission by Clement Ader in the year 1881 (from
Daniels, 2002): Listeners enjoy a performance of the Paris opera house transmitted by two
telephone lines. Ader patented this stereo telephone.
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 6/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Dolby Sorround Sound Formats
Dolby Sorround(for home media)
Mono OpticalSoundtrack
Dolby Digital 5.1 (AC−3 Transform Audio Coding)Dolby Digital Sorround EX (plus rear−center channel)
1976
Dolby SR1987
19991992
(improved dynamic range)
Dolby Stereo(left, center, right, surround)
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 7/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Dolby Stereo/Surround Playback
Source: “Surround Sound: Past, Present, and Future”, Dolby
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 8/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Dolby Digital Playback
Source: “Surround Sound: Past, Present, and Future”, Dolby
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 9/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Virtual Auditory Space using Headphones
Examples of Auditory Virtual Environments (AVEs):
• Dolby Axon → Audio Demonstration (www.dolby.com)
• IKA-SIM (Institut für Kommunikationsakustik)
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 10/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Head-Related Impulse Responses (HRIRs)
replacements
θ
x(k)
yr(k)
yℓ(k)
head-related impulse responses hr/ℓ(k, θk) describe thefree-field acoustical transfer from sound sources to thehuman ear canal – including reflection, diffraction, andrefraction of sound waves at head, pinnae, and torso:
yr/ℓ(k) =∑N
κ=0 hr/ℓ(κ, θk)x(k − κ)
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 11/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Numerous Applications of AVEs
• auditory displays, e.g., in aircrafts and flight simulators
• design and evaluation of performance rooms / music halls
• audio effects, e.g., “spatializers”
• music, games, television
• usability research and product-sound design, e.g., in cars
• augmented reality, e.g., in navigation
• virtual museum, virtual tourism, audiological self-screening
• tele-conferencing, tele-presence, tele-operation
• individual interactive movie sound
• www interfaces, e.g., second-life
• . . .
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 12/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Research Topics in Spatial Audio
◮ Rendering of 3D-Auditory Virtual Environments
◮ 3D-Audio Reproduction Systems (Beyond 5.1, 7.1, 10.2)
◮ Increased Compatibility of Sound Systems
◮ Standardization of Advanced Audio Formats and Codecs
◮ Spatial Sound Reproduction for Telecommunications:Telepresence, Hands-free Communication
◮ Binaural Sound for Digital Hearing Aids
◮ Acoustic Fiction or Physically Precise Rendering?
◮ ...
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 13/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Outline
◮ Spatial Audio Systems
◮ Digital Signal Processing
◮ Rapid Prototyping with Matlab
◮ Course Organization
◮ Previous Student Project: HRIR Demonstrator
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 14/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
What is a Signal ?
• A signal is a function of one or more variables, e.g., time orlocation:
x : t → x(t)
x : t → ~x(t)
x : (u, v) → x(u, v)
• Examples are:
• audio signals (captured by a microphone)
• image and video signals (captured by a camera)
• radio signals (captured by an antenna)
• biological signals (e.g., captured by electrodes)
• seismic signals (captured by accelerometers)
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 15/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Example: Speech Signal
0 1 2 3 4 5−0.8
−0.6
−0.4
−0.2
0
0.2
0.4
0.6
0.8
t/s
x(t)
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 16/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Example: CT Image
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 17/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Example: Seismic Signals
Earthquake on Feb 22, 2003 with centre in the Vogese and with magnitude
5.5 (http://sdac.hannover.bgr.de).
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 18/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
What is Signal Processing ?
• Signal processing is the art of modifying signals for thepurpose of analysis, transmission, synthesis, etc.
• Typical signal processing tasks are
• filtering (e.g. highpass, lowpass)
• signal analysis and pattern recognition (e.g. ASR)
• signal compression (e.g. GSM/UMTS voice codecs)
• signal enhancement (e.g. echo and noise reduction)
• signal synthesis (e.g. auditory virtual environments)
• Various applications: audio signal processing, image andvideo signal processing, signal processing for radiocommunications, medical signal processing, etc.
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 19/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
What is Digital Signal Processing ?
• In general, there are continuous (analog), discrete-time,and digital signals.
• Discrete-time signals are sampled continuous signals.
• Digital signals are sampled and quantized continuous signals.
• Digital signal processing is the modification of digitalsignals of by means of Personal Computers (PC’s), DigitalSignal Processors (DSP’s) or Application SpecificIntegrated Circuits (ASIC’s).
• Digital signal processing is ubiquitous (e.g. MP-3 player,mobile phones, car-control)
• In MATLAB, digital signals (floating-point most of the times)are represented by vectors and matrices.
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 20/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Outline
◮ Spatial Audio Systems
◮ Digital Signal Processing
◮ Rapid Prototyping with Matlab
◮ Course Organization
◮ Previous Student Project: HRIR Demonstrator
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 21/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
What is Rapid Prototyping ?
• First and quick (but not dirty!) implementation ofalgorithms, ideas, user interfaces, etc.
• Using tools which do not require extensive programmingeffort (e.g. provide for simple memory allocation)
• Using tools which provide for rich application-orientedlibraries and simple user-data interfaces
• No optimization w.r.t. memory, runtime efficiency, etc.
• Floating point arithmetics in most of the cases
• Platform independence (Operating System, Processor)
• Verification of algorithm functionality counts
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 22/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
What is MATLAB ?
“MATLAB is a high-performance language for technicalcomputing. It integrates computation, visualization, andprogramming in an easy-to-use environment where problemsand solutions are expressed in familiar mathematical notation.
Typical uses include
• Math and computation algorithm development
• Data acquisition, modeling, simulation, and prototyping
• Data analysis, exploration, and visualization
• Scientific and engineering graphics
• Application development, including graphical user interfacebuilding.”
(The Mathworks Inc.)
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 23/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Why MATLAB ?
• Easy-to-use interpreter language.
• MATLAB is the de facto industry standard for thedevelopment of signal processing and control.
• Many application libraries (’toolboxes’) available.
• Excellent and easy-to-use graphics, I/O, and userinterfaces.
• C/C++ code generation and real-time capabilities.
• Frequently used in textbooks for illustration and demopurposes.
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 24/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Why MATLAB ?
• Easy-to-use interpreter language.
• MATLAB is the de facto industry standard for thedevelopment of signal processing and control.
• Many application libraries (’toolboxes’) available.
• Excellent and easy-to-use graphics, I/O, and userinterfaces.
• C/C++ code generation and real-time capabilities.
• Frequently used in textbooks for illustration and demopurposes.
Disadvantages: price, licensing (check for student license!)Open source clone: OCTAVE (see www.octave.org)
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 24/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Outline
◮ Spatial Audio Systems
◮ Digital Signal Processing
◮ Rapid Prototyping with Matlab
◮ Course Organization
◮ Previous Student Project: HRIR Demonstrator
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 25/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Course Objectives
Basics of
Processing
Concepts of
SystemsDigital Signal Spatial Sound
Rapid Prototyping of
in Student Research Project"Signal Processing for Spatial Sound Control"
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 26/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Course Outline
◮ Digital Signal Processing• Discrete Signals and Systems• Spectral Analysis• MATLAB Basics / Tips and Tricks / FIR Filtering• z-Transform Analysis
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 27/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Course Outline
◮ Digital Signal Processing• Discrete Signals and Systems• Spectral Analysis• MATLAB Basics / Tips and Tricks / FIR Filtering• z-Transform Analysis
◮ Loudspeaker-Based Sound Systems
• “Audio Technology and Spatial Hearing” Lab• Room-Related Presentation of Auditory Scenes (Blauert)• Adaptive Filtering for Active Noise Control & Sound Projection
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 27/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Course Outline
◮ Digital Signal Processing• Discrete Signals and Systems• Spectral Analysis• MATLAB Basics / Tips and Tricks / FIR Filtering• z-Transform Analysis
◮ Loudspeaker-Based Sound Systems
• “Audio Technology and Spatial Hearing” Lab• Room-Related Presentation of Auditory Scenes (Blauert)• Adaptive Filtering for Active Noise Control & Sound Projection
◮ Binaural Sound Systems (Headphone-Oriented)
• Auditory Virtual Environments using HRIR/HRTF• Transaural System with Crosstalk Cancellation• Student Research Project (Rapid Prototyping Project)
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 27/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Course Info
• [email protected], (0234) 32 25392, ID/2/227
• Lecture with Integrated Exercises (1+1):Monday 16:00-17:30, ID/03/419 and ID/03/121 (CIP-Pool)
• Related Books:
• K.D. Kammeyer, K. Kroschel: “Digitale Signalverarbeitung”,Teubner, 2002
• Matlab Tutorial, The Mathworks, www.mathwork.com
• P. Vary, R. Martin, “Digital Speech Transmission”, Wiley, 2006
• F. Rumsey, “Spatial Audio”, Focal Press, 2001
• J. Blauert, “Spatial Hearing”, MIT Press, 1996
• Oral Exam: 25% DSP, 50% Audio, 25% Project, 5% Bonus
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 28/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Outline
◮ Spatial Audio Systems
◮ Digital Signal Processing
◮ Rapid Prototyping with Matlab
◮ Course Organization
◮ Previous Student Project: HRIR Demonstrator
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 29/31
Spatial Audio Systems Digital Signal Processing Rapid Prototyping Course Organization Student Project
Task Overview (Shortened)
Create a Matlab tool for the calculation of HRIRs (head-relatedimpulse responses) and headphone-based presentation of theirspatial sound attributes:
• The HRIRs as required in auditory virtual environments shallbe calculated according to algorithms described in literature.
• Using anechoic input signals, the HRIRs shall then beemployed to synthesize the impression of fixed and virtuallymoving (rotating) sound sources in space.
• Using Matlab’s “callback” mechanism, a user-friendly GUIshall be designed in order to control and evaluate the virtualauditory space.
Dr.-Ing. Gerald Enzner • Ruhr-Universität Bochum 30/31