Robust speech recognition in realistic hostile environments. Australia leads the world in the adoption of speech recognition technology but sadly lags in the development of the fundamental advances in the area. This research will help propel Australia to the forefront of new innovations in speech recognition technology and contributions to fundamental science. Our project will provide an excellent training ground for graduate students and researchers, with the real possibility of significant com ....Robust speech recognition in realistic hostile environments. Australia leads the world in the adoption of speech recognition technology but sadly lags in the development of the fundamental advances in the area. This research will help propel Australia to the forefront of new innovations in speech recognition technology and contributions to fundamental science. Our project will provide an excellent training ground for graduate students and researchers, with the real possibility of significant commercial benefit to the nation. The deployment of our system in the community will greatly enhance the defence and police forces ability for surveillance and security, and will provide new assistive aids to improve the quality of life and safety for the elderly and disabled.Read moreRead less
Enhanced Multilingual Speaker Recognition through the Incorporation of High-Level Features, Late Fusion and Discriminative Classification Methods. The development of robust multilingual speaker recognition systems will benefit the community through the elimination of fraud incurred by financial institutions and customers by enabling several person authentication applications such as: voice based signatures and document issuance; credit card verification by voice and secure over-the-phone financi ....Enhanced Multilingual Speaker Recognition through the Incorporation of High-Level Features, Late Fusion and Discriminative Classification Methods. The development of robust multilingual speaker recognition systems will benefit the community through the elimination of fraud incurred by financial institutions and customers by enabling several person authentication applications such as: voice based signatures and document issuance; credit card verification by voice and secure over-the-phone financial transactions. The technology will also assist in the protection of the community and safeguard Australia by enabling the implementation of the following: suspect identification using voice print; national security measures for combating terrorism by using voice to locate and track terrorists; preemptive criminal activity counter-measures; surveillance and secure building access by voice.Read moreRead less
Robust speaker recognition with reduced utterance duration and intersession variability. The development of robust and accurate speaker recognition systems will enable secure person authentication in over-the-phone financial transactions and benefit the community through the elimination of identity fraud incurred by customers and financial institutions. The technology will also assist in safeguarding Australia by enabling the implementation of suspect identification using voice and security meas ....Robust speaker recognition with reduced utterance duration and intersession variability. The development of robust and accurate speaker recognition systems will enable secure person authentication in over-the-phone financial transactions and benefit the community through the elimination of identity fraud incurred by customers and financial institutions. The technology will also assist in safeguarding Australia by enabling the implementation of suspect identification using voice and security measures for combating terrorism by using voice to locate and track terrorists. Our research at QUT Speech Research Lab is at the forefront of development in this field and will provide Australia with a technological advantage in the rapidly evolving global market for speaker recognition technology for person authentication applications.Read moreRead less
Robust Automatic Speaker Diarisation of Audio Documents by Exploiting Prior Sources of Information. Speaker Diarisation, the task of determining who spoke when, is a technology fundamental in deriving intelligent information from audio and multimedia resources. The requirement for efficient and accurate Speaker Diarisation systems, portable across different domains is heightened by the explosive growth of audio and multimedia archives online and throughout the world. This research will provide t ....Robust Automatic Speaker Diarisation of Audio Documents by Exploiting Prior Sources of Information. Speaker Diarisation, the task of determining who spoke when, is a technology fundamental in deriving intelligent information from audio and multimedia resources. The requirement for efficient and accurate Speaker Diarisation systems, portable across different domains is heightened by the explosive growth of audio and multimedia archives online and throughout the world. This research will provide the foundation for a commercial service of automatic Speaker Diarisation to be developed, growing Australia's impact on the information and communications technology (ICT) sector. The outcome of this research will also assist in the tracking of terrorist and unlawful activity by enabling effective intelligence gathering from different audio sources.Read moreRead less
Automatic detection and modelling of acoustic markers of speech timing. This project aims to create new automatic sensing, analysis and assessment of cognitive, affective, mental and physical state from voice for mobile and computing devices. This project expects to generate new understanding of the effects of these states on detailed timing indicators of speech motor control, and new signal processing and machine learning methods that best exploit it. Expected outcomes from this project include ....Automatic detection and modelling of acoustic markers of speech timing. This project aims to create new automatic sensing, analysis and assessment of cognitive, affective, mental and physical state from voice for mobile and computing devices. This project expects to generate new understanding of the effects of these states on detailed timing indicators of speech motor control, and new signal processing and machine learning methods that best exploit it. Expected outcomes from this project include a new and accurate deep neural network framework for learning, analysing and detecting human states from speech automatically using articulatory timing markers. This should provide significant benefits, such as individually-tailored, frequent and low-cost automatic detection, monitoring and analytics for adverse states.Read moreRead less
Audio Visual Speech Recognition. Even though significant advances have been made in automatic speech recognition using acoustic information, the recognition accuracies are still poor in noisy and hostile environments such as in crowds, traffic, factory floors etc. In many of these applications visual information is or can easily be made available in addition to the audio. The aim of this project is to achieve an order of magnitude improvement in speech recognition accuracies in adverse environme ....Audio Visual Speech Recognition. Even though significant advances have been made in automatic speech recognition using acoustic information, the recognition accuracies are still poor in noisy and hostile environments such as in crowds, traffic, factory floors etc. In many of these applications visual information is or can easily be made available in addition to the audio. The aim of this project is to achieve an order of magnitude improvement in speech recognition accuracies in adverse environments by joint processing and modelling of the acoustic modality with visual information in the form of lip shapes and movements. The outcomes will be useful in human computer interaction in adverse environments as well as in the transcription and mining of multimedia data.
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Robust feature extraction for automatic speech recognition. Speech is perhaps the most natural and efficient mode of communication for humans. Therefore, it has always been a dream for many people to communicate with machines via speech. Significant advances have been made in the last five decades in the area of automatic speech recognition. Though the currently available speech recognisers work reasonably well in noise-free office environments, their performance deteriorates drastically when th ....Robust feature extraction for automatic speech recognition. Speech is perhaps the most natural and efficient mode of communication for humans. Therefore, it has always been a dream for many people to communicate with machines via speech. Significant advances have been made in the last five decades in the area of automatic speech recognition. Though the currently available speech recognisers work reasonably well in noise-free office environments, their performance deteriorates drastically when they are deployed in real-life situations due to the presence of background noise and other distortions. The problem of robust speech recognition will be researched in this project. 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