Vector quantization approaches to nonlinear stochastic estimation. Many problems in health, economics, telecommunications and industrial control can be formulated as estimation problems with uncertain data. This project is aimed at developing a novel class of algorithms aimed at high complexity estimation problems. If successful, the project will provide new approaches to these problems.
Joint modelling and recognition of linguistic and paralinguistic speech information. A new modelling framework will be developed exploiting interdependence between linguistic and paralinguistic cues to improve automatic recognition of emotion-related information. Applications in the high-tech industry include automatic routing of angry telephone customers or pre-suicidal crisis centre callers to specialist operators/clinicians.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0560735
Funder
Australian Research Council
Funding Amount
$139,194.00
Summary
A Signal Simulation Facility for GNSS Receiver Design and Testing. The proposed Facility comprises a Global Navigation Satellite System (GNSS) RF Signal Simulator which allows laboratory testing of new signal tracking and navigation solution algorithms, under different scenarios. Simulation of the operation of current and future GPS satellites, and of the new European GNSS "Galileo", is vital for testing new receiver designs. For example, the Facility could be programmed to generate a GPS satell ....A Signal Simulation Facility for GNSS Receiver Design and Testing. The proposed Facility comprises a Global Navigation Satellite System (GNSS) RF Signal Simulator which allows laboratory testing of new signal tracking and navigation solution algorithms, under different scenarios. Simulation of the operation of current and future GPS satellites, and of the new European GNSS "Galileo", is vital for testing new receiver designs. For example, the Facility could be programmed to generate a GPS satellite signal with user-selectable physical variations in the signal path, including the presence of RF jamming sources, high atmospheric disturbances, diffraction effects and multipath. As many of the signal variations are rare and/or unpredictable, the Signal Simulator is the only means to carry out such tests.Read moreRead less
The development of new techniques for partial discharge monitoring and location in high voltage underground power cables. Increased utilization factors have caused a significant increase in the loading of high voltage distribution cables. This increased loading subjects cable insulation to increased stress which can degrade the insulation, cause cable failure and power loss to consumers. On-line cable insulation monitoring is required and partial discharge monitoring in cables provides a viable ....The development of new techniques for partial discharge monitoring and location in high voltage underground power cables. Increased utilization factors have caused a significant increase in the loading of high voltage distribution cables. This increased loading subjects cable insulation to increased stress which can degrade the insulation, cause cable failure and power loss to consumers. On-line cable insulation monitoring is required and partial discharge monitoring in cables provides a viable technique, but technical problems have prevented its application in on-line operation.
This project will develop techniques for such on-line monitoring. High frequency electrical sensors will be used to reduce interference and improve signal levels. Both a coarse alarm and a higher sensitivity monitor will be developed.
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Biologically Inspired Binaural Coupling for Selective Machine Hearing. This project aims to investigate biologically-inspired binaural coupling models in the context of the deep learning paradigm by formulating desirable higher level auditory structures as neural network sub-systems. This project expects to generate new knowledge for developing the next generation of robust speech processing systems that are capable of mimicking the selecting listening ability of humans when faced with realistic ....Biologically Inspired Binaural Coupling for Selective Machine Hearing. This project aims to investigate biologically-inspired binaural coupling models in the context of the deep learning paradigm by formulating desirable higher level auditory structures as neural network sub-systems. This project expects to generate new knowledge for developing the next generation of robust speech processing systems that are capable of mimicking the selecting listening ability of humans when faced with realistic noisy speech signals and the ‘cocktail party problem’ using innovative binaural feedback systems. This work should provide significant benefits, including improved voice biometrics and selective auditory attention capabilities in machines.Read moreRead less
Integrating biologically-inspired auditory models into deep learning. This project aims to discover how a biologically inspired auditory model can be tightly integrated into a state-of-the-art deep learning speech processing framework, to model, design and verify a deep learning based auditory model. Voice-based technologies, ranging from cochlear implants to smart homes, are growing at a rapid pace and speech interfaces are being integrated with all aspects of our lives. However, there is a gro ....Integrating biologically-inspired auditory models into deep learning. This project aims to discover how a biologically inspired auditory model can be tightly integrated into a state-of-the-art deep learning speech processing framework, to model, design and verify a deep learning based auditory model. Voice-based technologies, ranging from cochlear implants to smart homes, are growing at a rapid pace and speech interfaces are being integrated with all aspects of our lives. However, there is a growing demand to improve these voice-enabled services, making them more secure and less open to cyber-crime attack by unauthorised users. The project is expected to improve techniques for modelling and automatic processing of speech and audio signals, which should provide significant benefits, including improved voice biometrics and cochlear implants.Read moreRead less
Development of the applications of signal processing to mechanical problems and machine diagnostics. It is intended to extend research collaboration in the following areas of interest to both UTC and UNSW:
(1) Dynamics of gears for diagnostics and noise control
(2) Application of blind source separation techniques to mechanical problems
(3) Application of cyclostationary signal analysis techniques to machine diagnostics
(4) Determination of structural dynamic properties from response measure ....Development of the applications of signal processing to mechanical problems and machine diagnostics. It is intended to extend research collaboration in the following areas of interest to both UTC and UNSW:
(1) Dynamics of gears for diagnostics and noise control
(2) Application of blind source separation techniques to mechanical problems
(3) Application of cyclostationary signal analysis techniques to machine diagnostics
(4) Determination of structural dynamic properties from response measurements
(5) Diagnostics of diesel engines and other reciprocating machines.
This project will result in the publication of joint papers in each of these topics, and give material to form the basis of an application for at least one FAIR project in the area of gear noise control and diagnostics.Read moreRead less
Cancelling neighbouring voices for enhanced audio-visual collaboration. Cancelling neighbouring voices for enhanced audio-visual collaboration. This project aims to improve voice communication in immersive video conference technology for distance-based learning, using classrooms of students. research new theoretical approaches and develop new technology to transform the voice communication experience for co-located immersive video conferencing participants. When participants are co-located, two ....Cancelling neighbouring voices for enhanced audio-visual collaboration. Cancelling neighbouring voices for enhanced audio-visual collaboration. This project aims to improve voice communication in immersive video conference technology for distance-based learning, using classrooms of students. research new theoretical approaches and develop new technology to transform the voice communication experience for co-located immersive video conferencing participants. When participants are co-located, two major audio issues—significant acoustic echo and instability—can arise; these are barriers to the wider adoption of this mode of education delivery. The expected outcome is an immersive video conferencing application deployed by the partner organisation. A key benefit will be a significantly enhanced product that provides a commercial advantage as well as a solution to remote learning for Australian students and educators.Read moreRead less
Remote Sensing Based on Indirect GPS Signals. It is intended to utilize signals from the GPS satellite system, reflected from stationary objects (walls and water surfaces), to detect deformation or changed surface characteristics using the bistatic radar principle. The GPS receiving system consists of one or more signal detection components with antennas, as well as a processing device. The main objectives of the research are: the estimation of the power budget, developing techniques for system ....Remote Sensing Based on Indirect GPS Signals. It is intended to utilize signals from the GPS satellite system, reflected from stationary objects (walls and water surfaces), to detect deformation or changed surface characteristics using the bistatic radar principle. The GPS receiving system consists of one or more signal detection components with antennas, as well as a processing device. The main objectives of the research are: the estimation of the power budget, developing techniques for system modelling, developing techniques for simultaneous reception of signals from different satellites, and processing these signals with the aim of improving the spatial resolution, development of a demonstrator system, and evaluation of the system for selected remote sensing tasks.
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Speech recognition adaptation for low resource populations. Automatic speech recognition is an essential attribute of mobile devices and consumer electronics. Unfortunately, as these systems are trained with adult speech, they perform poorly when used by children and people with speaking difficulties. The lack of available training speech from these groups makes developing models for them difficult. We will investigate efficient model adaptation methods that use minimal training data to adapt ex ....Speech recognition adaptation for low resource populations. Automatic speech recognition is an essential attribute of mobile devices and consumer electronics. Unfortunately, as these systems are trained with adult speech, they perform poorly when used by children and people with speaking difficulties. The lack of available training speech from these groups makes developing models for them difficult. We will investigate efficient model adaptation methods that use minimal training data to adapt existing adult speech recognition models for use with children and people with speaking difficulties. The intended outcomes will improve access to automatic speech recognition systems for Australians whose communication with speech-controlled environmental and educational devices is currently restricted.Read moreRead less