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Acoustic Sensing & Design (ADS)

The focus of our K-project is on acoustic sensing and design. It combines both aspects of acoustic sensation, whereas sensing represents the passive side, and designing the active side respectively.

In this way recording, monitoring/analysis and playback are seen as an integrated approach for achieving better technological solutions and a higher customer benefit and satisfaction.
The consortium of this K-project is highly excellent in these fields as well on the scientific side as on the market side, and can therefore build an Austrian “center of gravity” for acoustic research and development, and is widely recognized in the scientific community.

This K-Project ASD is funded in the context of COMET – Competence Centers for Excellent Technologies by BMVITBMWFJStyrian Business Promotion Agency (SFG)Province of Styria – Government of Styria and The Technology Agency of the City of Vienna (ZIT). The programme COMET is conducted by Austrian Research Promotion Agency (FFG).




Environmental sound carries a tremendous amount of both valuable and important information, e.g. in communication and for safety. Nevertheless, noise and useful sounds are frequently mixed and cause stress, danger, and health problems. It is therefore not only our goal to find the means to reliably read acoustic information but also actively augment the audible meaning it bears.

Dealing with distinct information hidden in environmental sounds requires a skilful combination of high quality microphone (sensor) systems, sophisticated new signal processing and sound design techniques, future technology, and fundamental research. In this regard, substantial progress is only thinkable when a critical mass of several excellent scientific and industrial partners collaborates intensively. A successful former consortium (Project AAP) is expanded to exceed this critical mass.

In this project, all competence is brought together for successful sensing and design of environmental noises and sounds. This opens innovation potential for inexpensive and intelligent acoustic sensing and for the active design of an enhanced audio ambience. Intelligent sensing will increase safety by its rapid and remote detection of harmful incidents. Combined with computer simulations, sensing will further facilitate and speed up production processes. Augmented hearing is achieved by combining sensed information with the active generation of supportive sounds, e.g. in silent electrified cars whose physical state is otherwise hard to hear. Useful sounds such as speech are often corrupted by the acoustical environment. Existing enhancement methods will be improved by intelligent acoustic signal processing. Primary goals are increasing the audio quality, protecting listeners from harmful noises, and enlarging the recording distance to provide a bigger freedom of motion around recording devices.

To efficiently pursue the proposed goals, we propose the broad collaboration on several work packages with synergetic effects. The project consortium involves diverse sectors (research, development, product manufacturers, component manufacturers) incorporating the fundamental research and applied research expertise of the scientific partners and the research, development, and component as well as product manufacturing expertise of the industrial partners.

ASD Workpackages (IEM)

Project 1:

  • WP 1.1 MIMO Sound Synthesis
  • WP 1.2 eMobility
  • WP 1.3 Alternative Applications for ANC
  • WP 1.4 Crash-Panel

Workpackage 1.1: Hybrid Simulation Assisted MIMO Sound Synthesis for Automotive Interiors

The reduction of noise, vibration and harshness (NVH) is an important goal in the automotive industry. Calm cars lead to increased driving comfort and to less noisy streets. It is obvious that involving NVH considerations in a very early phase of the development process can improve NVH behaviour and save time and costs. For setting development targets, interior noise level and sound quality are thus parameters of main interest.
There are a lot of different tasks included in up to date engine and vehicle development, and in every state of the development process the influence on the interior noise wants to be assessed. Depending on the progress in the development, simulation and/or measurement data with different level of precision is available. For one point in the development some of the tasks might still be undone, some are only simulated, and others might already be measured. For interior sound synthesis this means that some of the tasks have to be estimated, others come from simulation and have already a higher degree of reliability and some might already come from measurements with a very high degree of data reliability.
Scope of this work package is the development of a new approach that enables engineers to estimate interior noise, already in a very early phase of the development process. This approach will allow audible prediction of interior noise from simulation as well as measurement data or a mixture of both.

During engine analysis, usually engine accelerations (speed-sweeps) are measured. Depending on the engine (e.g. passenger car, light duty, medium duty, heavy duty, …) the speed-sweeps differ between measurements. A first task in the work package will therefore be the synchronization of already measured NVH data, especially with respect to different engine accelerations. Additionally, engine speed-ups are simulated by sequentially combining simulations of different engine speeds. Also these kinds of speed-ups shall be covered in the synchronization approach. Following this approach, simulation results can be compared to corresponding measurement data.Using this tool, design modifications of engine or intake / exhaust system as well as changes of firewall isolation or transfer behaviour will become audible. This will allow necessary target settings for all noise sources and transfer functions to finally achieve the interior noise target. Prediction quality thereby will mainly be determined by input data quality. Reasonable predictions will already be possible in a very early stage of the development process where only simulation data is available. This allows for example comparison of different engine concepts already in very early simulation phase. As soon as first hardware is available, prediction accuracy will be enhanced by using measurement data for input to simulation (e.g. measured cylinder pressure) or by replacing simulation data by measurement data.

Furthermore, measurement data will be expanded by enhanced measurement methods. The task comprises sound-field measurements of the engine compartment and the vehicle interior as well as sound transfer estimation. With the new measurement method, we intend to measure the sound radiation in all 3 dimensions. We develop a suitable microphone array that allows radiation measurements of single engine compartments and of already built in engines. The influence of the measured radiating module onto other modules is investigated by a transfer path analysis (TPA), accounting for the fact that the transmission can either be airborne or structure-borne. To further reduce the measurement costs, we develop an inverse measurement setup where the excitation signal is produced in the car cabin and its influences are measured on parts where the actual vibration origin is expected. This way, all different transfer paths can be determined with one single measurement.

The simulated noises that have their origin in engine vibration mostly sound rather artificial. The addition of wind and rolling noise is expected to increase the naturalness of the interior noise. These noises mainly depend on the speed, on the design of the car and on the type of tires. Measurement methods to assess those noises have to be developed and parameterized characterizations need to be undertaken. With this, a sound generation tool will be developed that adds suitable wind and rolling noise to the simulated engine noise and makes the auditory evaluation of the interior noise more intuitive.

Status Report 2013


Calm cars lead to increased driving comfort and to less noisy streets. Thus, the reduction of noise, vibration and harshness (NVH) is an important goal in the automotive industry. An auditory evaluation of the interior noise in a very early stage of the design process will help to improve NVH behavior and save time and costs of the design process. This requires a simulation tool that estimates interior car noises before the prototype of a car is physically built. This includes modeling of wind and rolling noise (T3 & T4) as well as structure-borne (T2) and air-borne (T1) contribution of the engine to the interior noise.

Considering the in-situ sound radiation of an engine (T1) requires estimating the acoustic impedance of the engine compartment and the free-field radiation of the engine. Therefore, the radiated sound power of an engine in a free sound field has been investigated applying random and simulated excitation.


To achieve a rough statistical description of the radiated sound power, the surface velocity of an engine was assumed to be randomly distributed. In a Monte Carlo experiment with K=10000 realizations of normal distributed spherical harmonics coefficient sets were generated which result in a random surface velocity of a sphere. The radiated sound power was calculated for each coefficient set and the probability density function (pdf) of the radiated sound power was estimated by histograms for different ratios of radius to wave length.

Based on sound pressure data of a simulated engine (four different values of rotation speed and two different radii), the sound power estimation for different spherical sampling schemes was evaluated. The sound power calculated from the simulated pressure data using the full set of simulated data was taken as “ground truth”. The estimation error using only a subset of sampling points was investigated. This was done for several sampling schemes with different numbers of sampling points. For a statistical consideration of the estimation error each sampling scheme was randomly rotated 1000 times before estimating the sound power. Furthermore the estimation error using a far field assumption was investigated.


The model with random surface velocity yields limited standard deviation of sound power and its probability density function (pdf) follows a gamma distribution, cf. Figure 1. Therefore, the uncertainty of sound power with few measurements is probably limited.

Statistics over the sound pressure estimation based on the data of the simulated engine show that the standard deviation increases towards high frequencies, cf. Figure 2. Furthermore, it has shown that for a poor resolution of 4 measurement points 95% of the estimates are confined within a ± 4dB inaccuracy, and 50% of the estimates are confined within a ± 1dB inaccuracy. This confirms that free field sound power estimation with few sound pressure measurement points yields a limited error. Regarding the simulated data, only near fields (f < 125Hz) yield systematic deviations using the simplified far field estimation. Thus, the far field assumption is admissible for a large frequency range.

Workpackage 1.2: e-Mobility with Active Sound-Generation

Currently electric and hybrid vehicles are a very important topic for research and development. The field of interior and especially exterior sound engineering for vehicles driving in electric mode is a very new subject.

On the one hand low sound pressure levels in electrically driven cars evoke the issue that usually no feedback of the current operating condition is given to the driver. On the other hand this low interior noise provides a perfect basis for active sound generation (ASG). This might lead to a situation where customers could choose how their vehicle should sound like. While some drivers prefer the sound of a V8 engine another would like to have the experience of sitting in a spaceship.

Humans do not have a sense for velocity. Especially in heavy cars with good shock absorbers, one does not feel whether the car goes with 100 or 170 km/h. The auditory input is often the main velocity feedback that we get. In the case of electrical cars the acoustic feedback from the engine is no longer available. In order to account for that new situation, AVL is currently working on an ASG system that is able to give user defined audible feedback to the driver by using operating parameters like driving speed, target and actual acceleration. The change of operation parameters has to lead to immediate sound feedback, thus the processing unit between the parameter sensor and the ASG output has to have a low delay. The feedback sound itself has to be intuitive, easily interpretable, agreeable and not at least characteristic for a specific car company. We will collect user judgments from listening test with the expert listening panel (ELP) that was built up in the preceding AAP-project.

The exterior sound of an electrically driven car is very low, especially at velocities below 50 km/h. Therefore other traffic participants (e.g. pedestrians and cyclists) tend to miss those cars which might lead to an increase in traffic accidents. To prevent this expected increase of accidents, the scientific community and governments are currently debating on setting minimum noise level limits. Whatever the outcome of these discussions might be, a system that is able to generate exterior sound will be necessary. Again, the generated sound needs to fulfil requirements like being agreeable, still warning and again characteristic for a certain car company, and again listening tests with the ELP shall help to find and assess external sounds. Additionally a concept for the outside sound radiation will be developed.

Within this work package, a sound generation tool will be developed, to account for the new challenges in the sound design of electrical vehicles. This tool will incorporate parameterized sound models, with a reduced set of parameter which allow a fast and easy sound design.

A possible future scenario could be that people will be able to upload these sounds onto their cars, and depending on the daily mood the customer will choose the appropriate audible feedback. Thus the sound models have to be adoptable not only for different use cases but also for different users which again will be assessed by the ELP.

Finally, criteria for the objective assessment of the user perception are developed with the results of the ELP. The goal is to describe different sounds on a map and define axes that separate characteristic sounds. With this, user perception can be extrapolated and the definition and design of new sounds is facilitated.

Status Report 2013


Electric vehicles do not generate as much sound as vehicles with conventional combustion engines. On the one hand, the low exterior sound level yields potential risks for other traffic participants, e.g. pedestrians and cyclists, especially at vehicle velocities below 50 km/h. On the other hand, the low interior sound level does not provide auditory feedback about the current operation state of the vehicle, e.g. engine load and vehicle velocity, to the driver. In order to overcome these drawbacks, electric vehicles can be equipped with Active Sound Generation (ASG).


ASG requires a fast response to changing operation parameters. We achieve this by employing a real time synthesizer that can be controlled via standardized OBD or CAN-Bus protocols. The synthesizer provides 128 oscillators simultaneously, each one with frequency, gain, amplitude modulation, and phase modulation. The parameters of the oscillators depend on the engine speed and load, and they can be designed with the E-Vehicle Sound Generator Tool (still under development). In order to develop parameterized sound models for the interior sound with respect to comfort, acceptance and usability, run-up recordings of various conventional combustion engines have been analyzed. The analysis employs time-variant Vold-Kalman filters and suppresses the typical low-frequency rolling noise.


The figures below show spectrograms of a full-load run-up recording (left) and its synthesis (right) using the E-Vehicle Sound Generator Tool and the parametric real time synthesizer. Obviously, the synthesis matches the recording, except for the low-frequency rolling noise that is not desired to be modeled anyway.

Project 2:

  • WP 2.1 Distant Talking Speech Acquisition
  • WP 2.2 Close Talking Speech Acquisition
  • WP 2.3 Enhanced ANC for Headphones
  • WP 2.4 ADPCM
  • WP 2.5 Audio-Aided Process-Monitoring
  • WP 2.6 Adaptive Analogue Noise Cancelling

Workpackage 2.3: Enhanced Active Noise Control for Headphones

Headphones that diminish ambient noise are beneficial in a double sense. Firstly, they protect users from large sound levels from outside. Secondly, since the disturbing background noise is diminished, they reduce the need of harmfully loud music playback.
Closed headphones show good passive attenuation of high frequency noises from outside. However, there is no (or only very poor) passive attenuation of low frequency noises. Hence, active noise cancellation (ANC) methods are applied to yield a broadband attenuation of outside noises. In the Advanced Audio Processing (AAP) project, all main methods are investigated and suitable ANC-evaluation strategies are developed.

ANC headphones with a pure analogue feedback yield good results, but are limited to frequencies below 500 Hz because higher frequencies would drive the feedback unstable. This method is physically constrained by the group delay of the transfer function from the loudspeaker to the error sensing microphone inside the ear cup, and also loudspeaker linearization does not lead to an improved ANC.
Digital ANC headphones bear some advantages, because the inherent filter can adapt to changing conditions. However, the latency of conventional audio converters severely limits the ANC performance.

The first strategy in this work package is therefore to develop a digital ANC system with high speed data converters. Simulation results out of AAP show that the talk-through latency (ADC->DSP->DAC) should lie below 150μs to yield noise reduction up to 1000 Hz. Besides the ANC implementation, a suitable solution for music play back is investigated and applied to the prototype system.

The second strategy is to combine the fast analogue technique with adaptive methods known from digital ANC. Analogue adaptive filters are reviewed and elaborated, but they are not known to be used for ANC headphones. Instead of the latter approach where a serial circuit is used, we suggest parallel ANC filters. The more filters that are being used, the more accurately the outside noise can be cancelled. However, the number of used filters is restricted by realizable hardware expenses.

Firstly, theoretical considerations of the AAP are picked up and the maximally achievable performance is outlined. Secondly, different wearing conditions (leakage) are considered and finally a limited number of (analogue) applicable filters are chosen and their ANC performance is simulated. After the simulation, a hybrid implementation of the analogue filters and a digital adaptation unit is designed and finally a pure analogue implementation is targeted. In all three stages (simulation, hybrid and pure analogue) music play back is considered, too.

Status Report 2013


Headphones with active noise control (ANC) sense the undesired ambient noise and play back an ‘anti-noise’ with the same wave form but opposite sign. Inside the headphones the noise and the ‘anti-noise’ interfere destructively and cancel each other. Digital methods would be of great advantage in ANC headphones, because they allow easily recording, analyzing and manipulating the sensed noise signal. Therefore digital ANC-headphones could react on changing acoustical and/or signal conditions online.

However, conventional audio-codecs for analogue to digital conversion (ADC) and digital to analog conversion (DAC) have a too large latency. Consequently, the anti-noise would arrive too late and noise control would be deteriorated. In the first task of this work package, we therefore assemble a digital prototype system with low-latency.


In the preceding K-project AAP, we investigated the influence of the latency onto the noise-cancelling performance by simulations. We found out that only systems with latency below 150 µs yield ANC that is comparable to existing analogue approaches. Conventional audio-codecs, however, have a latency of at least 720µs.

The first step is identifying the components that are responsible for the large latency in existing hardware packages. Once, these components are identified, the second step is to look for alternative solutions (also outside the field of audio components). The third step is to interface the new solution with audio-processing hardware.


The reasons for the large latency in common audio-codecs are the integrated linear phase anti-aliasing and reconstruction filters. Linear phase means that all signal components are equally delayed, but equally long delayed. For ANC headphones it does not matter if some signal parts are more delayed than others. It is more important that all signal parts are delayed as little as possible. Therefore, we choose ADCs and DACs without integrated linear phase filters and design our own anti-aliasing and reconstruction filters with minimum phase (i.e. minimum delay). The chosen ADC and DACs are interfaced with the audio processor via standardized serial protocols. The ADC converts three signals per headphones channel: (i) A reference of the noise that is sampled with a microphone outside the headphones. (ii) The residual noise that is sampled with a microphone inside the headphones. (iii) The music signal. The crucial point in programming the interface is that the reference signal is filtered and sent to the DAC as soon as the new sample is available.

By the above described means we manage to reduce the talkthrough latency of the digital system to approx. 52 µs which is well below the target value of 150 µs.

Workpackage 2.4: Low-Delay High-Quality Audio Codec

Audio compression is the most important digital signal processing component in professional wireless digital microphone systems. Most wireless digital microphone system use a modified version of the G.722 CODEC, the ADPCM (adaptive differential pulse coded modulation) compression algorithm that is also used in GSM cellular systems for speech compression. The main focus of the project is the development of advanced and novel signal processing methods aimed at improving standard CODECs in terms of latency and audio quality for a vast variety of wideband and highly dynamic music signals, while maintaining a low data rate.

Status Report 2013


Audio compression is the most important digital signal processing component in professional wireless digital microphone systems. Most wireless digital microphone systems use modified versions of the G.722 standard, the ADPCM (adaptive differential pulse coded modulation) compression algorithm used in the GSM cellular system for speech compression. The main focus of the project is the development of advanced and novel signal processing methods aimed at improving current audio CODECs (coder-decoder) in terms of latency and audio quality for a vast variety of wideband and highly dynamic music signals, while maintaining a low data rate compatible with professional wireless microphone applications.


State of the art low latency audio CODECs consist of several functional blocks that include, analysis/synthesis filter banks, linear prediction, low complexity quantization and dithering or noise shaping schemes. In order to improve the overall performance these individual functional blocks are the subject of research.

However, the resulting overall system has to stay within well-defined performance measures that include the maximum data rate, overall CODEC latency, algorithmic complexity, transmission error robustness and most important the obtained audio quality.

In order to fine-tune parameters of the CODEC and for optimization of its components the audio quality is evaluated using the perceptual evaluation of audio quality (PEAQ) measure. The audio quality of the final implementation is verified with subjective listening tests.

The best performing CODEC configuration will be developed in multi-host C code.


As the parameter optimization is based on the obtained PEAQ values it was necessary to verify their validity. Therefore, the results from informal listening tests were correlated with the PEAQ values, leading to the conclusion that it is possible to identify trends in quality, but not the actual audio quality on an absolute scale.

Further, a state of the art low delay audio CODEC using closed loop prediction in lattice structure was implemented as a starting point for further developments. This CODEC was adapted and improved with respect to transmission error robustness and the quantizer is optimized to yield maximum SNR using a Max-Lloyd optimization. The audio quality obtained using the current implementation (working name: ERR8) was compared against the audio quality of other commercially available CODECS (see figure below).

The current implementation outperforms the other tested CODECs for most samples and has zero algorithmic latency but has quality deficits when dealing with highly transient signals. Strategies to overcome the deficits for highly transient signals include advanced noise shaping methods and increased prediction order.

Workpackage 2.5: Audio-aided Process-Monitoring

The increasing complexity in combustion engines requires consistent and smart test methodologies and test technologies in which it is crucial to consider manufacturing and assembling processes related to modern engine technologies. End of line testing is therefore one of the most important topics for engine manufacturers to assess production quality. Evaluation of the production quality within defined limits is performed during two different test set-ups. The first is inspecting motored engines without firing during so called “Cold Tests”. The second possibility is the End of Line Engine Hot Test System which is an integrated part of the production environment and represents a key factor to ensure the product and production quality with lowest possible efforts and costs. Up to now also subjective evaluations were performed during end of Line testing to ensure the quality of the engines. To increase the security of employees, test cells will not be accessible during non-safe engine operation in future. This leads to the issue that no subjective testing will be possible during End of Line tests. Therefore the need for an automated acoustic assessment of engines is tremendous.

Scope of this work package is the development of such an automated acoustic assessment that will allow a high quality noise assessment during end of Line testing. To achieve this challenging target some big issues have to be solved.

The first big challenge is the very noisy test cell environment. As End of Line tests are not designed to provide free field conditions for measurement, the vast amount of reflections in the chamber have to be considered. This leads to the necessity of defining a measurement setup that allows high quality measurement also in such a noisy environment.

As an up-to-date combustion engine is a very complex machine, a lot of different and very complex noise phenomena can occur. Some of them are completely normal and others might indicate a malfunction of the engine. The methodology that will be developed within this workpackage has to take this into account. A very crucial topic for analysis is for instance the combustion analysis. Phenomena like knocking on Diesel engines might be completely normal for one engine and might show problems in the injection system for another engine. The same is valid for engine roughness, gear whine or piston slap phenomena. Phenomenon based identification and assessment is therefore a very crucial point of this work package.

ASD Team (IEM)

Brandner, Manuel DI

+43 316 389 3254

Frank, Matthias DI Ph.D.

+43 316 389 3354

Höldrich, Robert O.Univ.Prof. Mag. DI Dr.

+43 316 389 115

Luig, Johannes DI

+43 316 389 3356

Pomberger, Hannes DI

+43 316 389 3747

Schörkhuber, Christian DI

+43 316 389 3800

Sontacchi, Alois DI Dr.

+43 316 389 3548

Vogt, Katharina Mag. Dr.

+43 316 389 3740

Zaunschirm, Markus DI

+43 316 389 3604

Zotter, Franz DI Dr.

+43 316 389 3382

ASD Publications (IEM)


  • Matthias Frank, "Simple Uncertainty Prediction for Phantom Source Localization", DAGA 2015, Nuremberg, March 2015.
  • Franz Zotter, Matthias Frank, Christian Haar, "Spherical microphone array equalization for Ambisonic playback", DAGA 2015, Nuremberg, March 2015.
  • Markus Zaunschirm, Matthias Frank, "Sound Focusing in Rooms Using a Source with Controllable Directivity", DAGA 2015, Nuremberg, March 2015.
  • Matthias Frank, Franz Zotter, Alois Sontacchi, "Producing 3D Audio in Ambisonics", AES 57th Conference on The Future of Audio Entertainment Technology, Hollywood CA, March 2015.


  • Manuel Brandner, Markus Flock, Martin Schörkmaier, "Feedback Loop Shaping for Active Noise Control With Constraints of the Worst Case Secondary Paths", 6th Congress of the Alps Adria Acoustics Association, Graz, October 2014.
  • Christian Schörkhuber, Philipp Hack, Markus Zaunschirm, Franz Zotter, Alois Sontacchi, "Localization of multiple acoustic sources with a distributed array of unsynchronized first-order Ambisonics microphones", 6th Congress of the Alps Adria Acoustics Association, Graz, October 2014.
  • Hannes Pomberger, Franz Zotter, Robert Höldrich, Stephan Brandl , "Estimating uncertainty in pressure-based sound power measurement due to spatial sampling and near fields", 6th Congress of the Alps Adria Acoustics Association, Graz, October 2014.
  • Markus Zaunschirm, Matthias Frank, Alois Sontacchi, Paolo Castiglione, "Audio Quality: Comparision of PEAQ and formal listening test results", 6th Congress of the Alps Adria Acoustics Association, Graz, October 2014.
  • Matthias Frank, Alois Sontacchi, Stephan Brandl, Robert Höldrich, "Sound for Electric Cars: What can we learn from combustion engines?", 6th Congress of the Alps Adria Acoustics Association, Graz, October 2014.
  • Matthias Frank, "How to Make Ambisonics Sound Good", Forum Acusticum, Krakow, September 2014.
  • Franz Zotter, Matthias Frank, Andreas Fuchs, Daniel Rudrich, "Preliminary study on the perception of orientation-changing directional sound sourcesin rooms", Forum Acusticum, Krakow, September 2014.
  • Markus Guldenschuh, "Least-Mean-Square Weighted Parallel IIR Filters in Active-Noise-Control Headphones", EUSIPCO 2014, Lisbon, Sept. 2014.
  • Matthias Frank, Franz Zotter, Alois Sontacchi, Stephan Brandl, Christian Kranzler, "Comprehensive Array Measurements of In-Car Sound Field in Magnitude and Phase for Active Sound Generation and Noise Control", SAE Int. J. Passeng. Cars – Electron. Electr. Syst. 7(2), August 2014.
  • Markus Guldenschuh, Raymond de Callafon, "Detection of Secondary-Path Irregularities in Active Noise Control Headphones", IEEE Transactions on Audio, Speech, and Language Processing 22(7), pp. 1148-1157, July 2014.
  • Alois Sontacchi, Matthias Frank, Franz Zotter, Christian Kranzler, Stephan Brandl, "Sound Optimization for Downsized Engines", SAE Technical paper 2014-01-2040, June 2014.
  • Matthias Frank, "Localization Using Different Amplitude-Panning Methods in the Frontal Horizontal Plane", EAA Joint Symposium on Auralization and Ambisonics, Berlin, April 2014.
  • Nicolas Epain, Craig T. Jin, Franz Zotter, "Ambisonic Decoding with Constant Angular Spread", EAA Symposium on Auralization and Ambisonics, Berlin, April 2014.
  • Franz Zotter, Matthias Frank, Matthias Kronlachner, Jung-Woo Choi, "Efficient Phantom Source Widening and Diffuseness in Ambisonics", EAA Symposium on Auralization and Ambisonics, Berlin, April 2014.
  • Georgios Marentakis, Franz Zotter, Matthias Frank, "Vector-Base and Ambisonic Amplitude Panning: A Comparison Using Pop, Classical, and Contemporary Music", EAA Symposium on Auralization and Ambisonics, Berlin, April 2014.
  • Markus Zaunschirm, Franz Zotter, "Measurement-based Modal Beamforming using Planar Circular Microphone Arrays", EAA Symposium on Auralization and Ambisonics, Berlin, April 2014.
  • Matthias Frank, "Elevation of Horizontal Phantom Sources", DAGA 2014, Oldenburg, March 2014.
  • Florian Wendt, Matthias Frank, Franz Zotter, "Panning with Height on 2, 3, and 4 Loudspeakers", 2nd International Conference on Spatial Audio (ICSA), Erlangen, February 2014.


  • Markus Guldenschuh, "Secondary-path models in adaptive-noise-control headphones," 3rd International Conference on Systems and Control (ICSC), pp.653-658, Algiers, October 2013.


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