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
Active Sound Control and Noise Cancellation over Space. This project aims to address the critical issues for creating acoustic quiet zones in a noisy environment. It will provide novel signal processing theory for further development of active noise cancellation techniques over spatial regions. New technologies developed from this project are expected to underpin the future development of acoustic signal processing research and will have a broad range of applications such as reduction of noise i ....Active Sound Control and Noise Cancellation over Space. This project aims to address the critical issues for creating acoustic quiet zones in a noisy environment. It will provide novel signal processing theory for further development of active noise cancellation techniques over spatial regions. New technologies developed from this project are expected to underpin the future development of acoustic signal processing research and will have a broad range of applications such as reduction of noise inside cars, creation of individual quiet zones in passenger planes and mitigation of acoustic noise made by industrial plants to neighbouring suburbs. The outcomes from this proposal will also have economic importance as it can reduce the health risk posed to people working or living in noisy environments.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE150100363
Funder
Australian Research Council
Funding Amount
$330,000.00
Summary
The cocktail party problem: Advancing binaural localisation techniques. This project aims to advance fundamental research in source localisation by using a binaural system with two sensors to mimic human listening capabilities. It will provide new theory of source localisation features, novel signal processing techniques and design of binaural devices for localising sound sources in a cluttered acoustic environment. New technologies developed from this project will endeavour to lead to further d ....The cocktail party problem: Advancing binaural localisation techniques. This project aims to advance fundamental research in source localisation by using a binaural system with two sensors to mimic human listening capabilities. It will provide new theory of source localisation features, novel signal processing techniques and design of binaural devices for localising sound sources in a cluttered acoustic environment. New technologies developed from this project will endeavour to lead to further development of binaural audio research and will have a broad range of applications, such as hearing aids, personal sound amplification products and humanoid robots. The project aims to enable people wearing binaural devices or robots having two artificial ears to localise sounds and to follow a conversation in realistic situations.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120102210
Funder
Australian Research Council
Funding Amount
$350,333.00
Summary
Feedback control as a tool for enhanced neuroprosthetic stimulation. The aim is to use control theory tools to find optimal stimulation parameters to use in a bionic implant. This project will lead to improvements in understanding of mechanisms underlying electrical stimulation and to improvements in medical bionics technologies.
New entropy measures of short term signals for smart wearable devices. This project aims to improve reliability and accuracy of wearable devices by developing a new set of computationally efficient algorithms. Wearable devices can be very effective in remote and continuous monitoring to detect short or bursty anomalous events. Present devices are unable to detect such events effectively due to limited capability in processing short length signal. This project will provide computationally efficie ....New entropy measures of short term signals for smart wearable devices. This project aims to improve reliability and accuracy of wearable devices by developing a new set of computationally efficient algorithms. Wearable devices can be very effective in remote and continuous monitoring to detect short or bursty anomalous events. Present devices are unable to detect such events effectively due to limited capability in processing short length signal. This project will provide computationally efficient algorithms for signal quality analysis and enhanced feature extraction methods in resource constrained wearable devices. This will improve the reliability and performance of wearable devices for adoption in intelligent decision-making systems.Read moreRead less
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.
Modelling of neural plasticity for enhanced performance of brain-machine interfaces. Plasticity of the brain is one of the great scientific challenges of neuroscience. The aim of this project is to model the synaptic changes that occur with reward-modulated spike-timing-dependent plasticity and apply the model to developing plasticity targeted brain-machine interfaces. The significance of this approach is that such plasticity targeted techniques provide the prospect of taking advantage of the un ....Modelling of neural plasticity for enhanced performance of brain-machine interfaces. Plasticity of the brain is one of the great scientific challenges of neuroscience. The aim of this project is to model the synaptic changes that occur with reward-modulated spike-timing-dependent plasticity and apply the model to developing plasticity targeted brain-machine interfaces. The significance of this approach is that such plasticity targeted techniques provide the prospect of taking advantage of the underlying neural plasticity to optimise the form of the neural recording and electrical stimulation. The outcomes will be to greatly improve the performance of brain-machine interface in terms of measures such as the number and sensitivity of channels, as well as robustness and reliability.Read moreRead less
Continuous wave excitation for low power Magnetic Resonance Imaging. This project aims to augment the capabilities of Magnetic Resonance Imaging (MRI) systems, using continuous wave (CW) transmission and signal reception, to image objects using very low excitation power. Any given MRI sequence tries to solve an inverse problem, involving estimation of some subset of hidden states and parameters of the system, given the observed data. Using transient and steady-state CW magnetisation dynamics to ....Continuous wave excitation for low power Magnetic Resonance Imaging. This project aims to augment the capabilities of Magnetic Resonance Imaging (MRI) systems, using continuous wave (CW) transmission and signal reception, to image objects using very low excitation power. Any given MRI sequence tries to solve an inverse problem, involving estimation of some subset of hidden states and parameters of the system, given the observed data. Using transient and steady-state CW magnetisation dynamics to solve inverse problems is expected to advance technology toward lower power, lower cost solutions for MRI scanners in healthcare and industrial applications, including materials science and mineral processing.Read moreRead less
Sound Control Panels Made of Digital Acoustics Elements. This project aims to pioneer a new generation of smart sound control panels made of digital acoustics elements for broadband sound control. The project expects to generate a break-through mechanistic understanding of energy dissipation among the acoustical, mechanical and electrical components in the proposed devices. It is expected that these devices will have superior sound absorption performance from 50 Hz to 10 kHz, and will be low cos ....Sound Control Panels Made of Digital Acoustics Elements. This project aims to pioneer a new generation of smart sound control panels made of digital acoustics elements for broadband sound control. The project expects to generate a break-through mechanistic understanding of energy dissipation among the acoustical, mechanical and electrical components in the proposed devices. It is expected that these devices will have superior sound absorption performance from 50 Hz to 10 kHz, and will be low cost, compact (<10 mm thick), environmentally sustainable, clean (fibreless), and be adaptive to environments. It will provide a solution for broadband sound control, which is critical for many domestic, industry, and military applications to create a quieter and more comfortable sound environment.Read moreRead less
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.