Bio-inspired speech analysis: Specialised information processing of vocalisations in the auditory brainstem. This project has the potential to benefit bionic ear and hearing aid users through the development of signal processing methods that mimic the amazing abilities of the brain. Speech perception performance by bionic ear users has reached a plateau and these new strategies could produce the breakthrough needed to provide the next increase in performance. The benefit for greater improved hea ....Bio-inspired speech analysis: Specialised information processing of vocalisations in the auditory brainstem. This project has the potential to benefit bionic ear and hearing aid users through the development of signal processing methods that mimic the amazing abilities of the brain. Speech perception performance by bionic ear users has reached a plateau and these new strategies could produce the breakthrough needed to provide the next increase in performance. The benefit for greater improved hearing has enormous benefit and potential for improving the quality of life of the hearing impaired, especially those with severe and profound hearing loss. In addition, the algorithms may provide more robust automatic speech recognition, making this technology more useful in everyday situations; the markets that this would open up are enormous.Read moreRead less
Frequency-related features derived from phase spectrum for robust speech recognition. Though the currently available speech recognizers work reasonably well in noise-free environments, their performance deteriorates drastically even in the presence of a small amount of noise. In order to overcome this problem, new frequency-related features are proposed in this project for speech recognition. These features are derived from the phase spectrum of the speech signal, and are expected to be robust t ....Frequency-related features derived from phase spectrum for robust speech recognition. Though the currently available speech recognizers work reasonably well in noise-free environments, their performance deteriorates drastically even in the presence of a small amount of noise. In order to overcome this problem, new frequency-related features are proposed in this project for speech recognition. These features are derived from the phase spectrum of the speech signal, and are expected to be robust to the additive noise distortion. These features will make the speech recognizer less sensitive to noise and will enhance its utility in a number of applications in the telecommunication and business world.Read moreRead less
Fixed and variable-length segment vocoders for very low bitrate speech coding. Reliable and secure voice communication is an important aspect of military and defence operations. In order to reduce the possibility of interception, low power transmitters are normally used for radio communications, where the bandwidth is often very low. Military voice communication, therefore, requires the coding of speech at very low bitrates. Our research proposal aims to develop speech coders that can operate ....Fixed and variable-length segment vocoders for very low bitrate speech coding. Reliable and secure voice communication is an important aspect of military and defence operations. In order to reduce the possibility of interception, low power transmitters are normally used for radio communications, where the bandwidth is often very low. Military voice communication, therefore, requires the coding of speech at very low bitrates. Our research proposal aims to develop speech coders that can operate at lower bitrates and reproduce speech of high quality and intelligibility. This is highly beneficial to the defence forces of Australia as it will permit the use of high-grade encryption technology to improve the security of transmission.Read moreRead less
Adaptive learning of spatiotemporal patterns: Development of multi-layer spiking neuron networks using Hebbian and competitive learning. The aim of this project is to develop a method for recognising patterns that change in time. The development of a reliable method that is fast and robust to noise will have wide application in many areas, especially computer speech recognition where timing plays a crucial role. Building-blocks similar to those in the brain (spiking neurons) will be used. Aut ....Adaptive learning of spatiotemporal patterns: Development of multi-layer spiking neuron networks using Hebbian and competitive learning. The aim of this project is to develop a method for recognising patterns that change in time. The development of a reliable method that is fast and robust to noise will have wide application in many areas, especially computer speech recognition where timing plays a crucial role. Building-blocks similar to those in the brain (spiking neurons) will be used. Automatic techniques will be used to teach groups of spiking neurons the differences between sequences of events by adjusting connections between them. The significance of this approach is that it captures information about timing that is missed in existing techniques.Read moreRead less
Adaptive learning in networks of spiking neurons for recognising patterns that change with time. The aim of this project is to develop a method for recognising patterns that change with time. Building-blocks similar to those in the brain (spiking neurons) will be used. Automatic techniques will be developed to teach groups of spiking neurons the differences between sequences of events by adjusting connections between neurons. The significance of this approach is that it captures information abou ....Adaptive learning in networks of spiking neurons for recognising patterns that change with time. The aim of this project is to develop a method for recognising patterns that change with time. Building-blocks similar to those in the brain (spiking neurons) will be used. Automatic techniques will be developed to teach groups of spiking neurons the differences between sequences of events by adjusting connections between neurons. The significance of this approach is that it captures information about timing that is missed in existing techniques. The development of a reliable method that is fast and robust to noise will have wide application in many areas, especially computer speech recognition where timing plays a crucial role.Read moreRead less
Temporal Pattern Learning and Recognition in Neural Systems. This project is relevant to the National Research Priority area of Frontier Technologies and addresses fundamental cross-disciplinary issues of how neural systems learn patterns that change with time, which is at the cutting edge of intelligent processing systems. Applications are in rapidly growing fields of automatic speech processing, robotics, machine learning and intelligent systems, all with applications in areas of economic impo ....Temporal Pattern Learning and Recognition in Neural Systems. This project is relevant to the National Research Priority area of Frontier Technologies and addresses fundamental cross-disciplinary issues of how neural systems learn patterns that change with time, which is at the cutting edge of intelligent processing systems. Applications are in rapidly growing fields of automatic speech processing, robotics, machine learning and intelligent systems, all with applications in areas of economic importance. Application to cochlear implant speech processing will provide benefit for the hearing impaired. The project will provide students with training at an international level within Australia, thus helping ensure Australia maintains and extends its science and technology base into the future.Read moreRead less