Linkage Infrastructure, Equipment And Facilities - Grant ID: LE100100211
Funder
Australian Research Council
Funding Amount
$650,000.00
Summary
The Big Australian Speech Corpus: An audio-visual speech corpus of Australian English. Contemporary speech science and technology are driven by the availability of large speech corpora. While audio databases exist for languages spoken in America, Europe and Japan, there is currently no large auditory-visual database of spoken language, and certainly not one for Australian English. Here we will establish the Big Australian Speech Corpus, which will support a speech science research and developmen ....The Big Australian Speech Corpus: An audio-visual speech corpus of Australian English. Contemporary speech science and technology are driven by the availability of large speech corpora. While audio databases exist for languages spoken in America, Europe and Japan, there is currently no large auditory-visual database of spoken language, and certainly not one for Australian English. Here we will establish the Big Australian Speech Corpus, which will support a speech science research and development using Australian English and facilitate the development of Australian speech technology applications from automatic speech recognition and text-to-speech synthesis used in taxi and other ordering services, to hearing prostheses and talking head aids for learning-impaired children, and a range of security and forensic applications.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220100265
Funder
Australian Research Council
Funding Amount
$417,000.00
Summary
A closed-loop human–agent learning framework to enhance decision making. This project aims to design a foundational human–agent learning framework to augment the decision making process, using reinforcement and closed-loop mechanisms to enable symbiosis between a human and an artificial-intelligence agent. It envisages significant new technologies to promote controllability and efficient and safe exploration of an environment for decision actions – drastically boosting learning effectiveness and ....A closed-loop human–agent learning framework to enhance decision making. This project aims to design a foundational human–agent learning framework to augment the decision making process, using reinforcement and closed-loop mechanisms to enable symbiosis between a human and an artificial-intelligence agent. It envisages significant new technologies to promote controllability and efficient and safe exploration of an environment for decision actions – drastically boosting learning effectiveness and interpretability in decision making. Expected outcomes will benefit national cybersecurity by improving our understanding of vulnerabilities and threats involving decision actions, and by ensuring that human feedback and evaluations can help prevent catastrophic events in explorations of dynamic and complex environments.Read moreRead less