Towards realistic verbal interactions between people and computers-a probabilistic approach. This project aims to facilitate natural spoken interactions between people and computer systems, addressing obstacles to the acceptance of these systems. We will investigate computational models for relevant aspects of spoken dialogue, which will be implemented in computer systems for diverse tasks (for example, home devices and phone-enabled services).
Discovery Early Career Researcher Award - Grant ID: DE120102900
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
WikiLinks: web-scale linking and fact extraction with Wikipedia. Wikipedia is the most popular web site for finding facts, but articles about local or specialist topics are often missing or unreliable. WikiLinks will use artificial intelligence to link names in text to corresponding Wikipedia articles, allowing us to automatically create and augment Wikipedia content by summarising existing material on the web.
Beyond the grammar checker: automated copy-editing assistance. In the traditional publishing process, copy-editors correct and polish what authors write, but financial pressures mean that copy-editing is often considered a luxury. This project uses natural language processing and artificial intelligence techniques to develop technology that automates a significant proportion of the copy editing task.
Responding to requests and situations in assistive computer systems - a decision-theoretic approach. This project aims to enable computer agents to respond appropriately to people's spoken requests and circumstances (e.g., ask questions or perform actions). This project will investigate computational models for response generation, which will be implemented in assistive computer systems, thus enabling people to interact more easily with these systems.
Perceptually-motivated speech parameters for concurrent coding and noise-robust distributed recognition of human speech for mobile telephony systems. With speech being a simple and natural form of communication, speech recognition technology is being widely used in mobile phones. Nowadays, consumers can interact with remote systems via spoken words. This project will develop remote speech recognition with better accuracy and noise-robustness while using the existing mobile phone infrastructure.
Improved syntactic and semantic analysis for natural language processing. This project aims to improve the accuracy of syntactic and semantic analysis of natural language for automatic extraction of meaning from text. Many data mining and information extraction applications rely on syntactic and semantic analysis. Current analysis approaches are limited because they require expensive manually-labelled data. The project plans to develop new indirectly-supervised approaches to overcome this labell ....Improved syntactic and semantic analysis for natural language processing. This project aims to improve the accuracy of syntactic and semantic analysis of natural language for automatic extraction of meaning from text. Many data mining and information extraction applications rely on syntactic and semantic analysis. Current analysis approaches are limited because they require expensive manually-labelled data. The project plans to develop new indirectly-supervised approaches to overcome this labelled data bottleneck. By integrating information from large text corpora and structured databases, the project aims to minimise the reliance on manually-labelled data for training natural language processing systems. Automatic methods for syntactic and semantic analysis would have a wide range of applications in extracting information from large collections of unstructured data, such as hospital patient records or social media.Read moreRead less
The next generation speaker recognition system. The next generation of speaker recognition technologies developed through this project will enable secure person authentication by voice in financial transactions and benefit the community through the elimination of identity fraud. This project will safeguard Australia by identifying criminal suspects using their voice and combat terrorism by using voice to locate and track terrorists.
Subband centroids and deep neural networks for robust speech recognition. This project aims to improve the robustness and accuracy of automatic speech and speaker recognition systems. Though these systems work reasonably well in noise-free environments, their performance deteriorates drastically even in the presence of a small amount of noise. To overcome this problem, this project proposes a missing-feature approach for robust speech and speaker recognition. This approach is expected to make th ....Subband centroids and deep neural networks for robust speech recognition. This project aims to improve the robustness and accuracy of automatic speech and speaker recognition systems. Though these systems work reasonably well in noise-free environments, their performance deteriorates drastically even in the presence of a small amount of noise. To overcome this problem, this project proposes a missing-feature approach for robust speech and speaker recognition. This approach is expected to make the speech and speaker recognition systems less sensitive to additive background noise and make them more useful in telecommunications and business.Read moreRead less
Explaining the outcomes of complex computational models. This project aims to develop new algorithms that automatically generate explanations for the results produced by complex computational models. In recent times, these models have become increasingly accurate, and hence pervasive. However, the reasoning of Deep Neural Networks and Bayesian Networks, and of complex Regression models and Decision Trees is often unclear, impairing effective decision making by practitioners who use the results o ....Explaining the outcomes of complex computational models. This project aims to develop new algorithms that automatically generate explanations for the results produced by complex computational models. In recent times, these models have become increasingly accurate, and hence pervasive. However, the reasoning of Deep Neural Networks and Bayesian Networks, and of complex Regression models and Decision Trees is often unclear, impairing effective decision making by practitioners who use the results of these models or investigate the decisions made by the systems. Practical benefits of clear decision making reasoning by complex computational models include reduced risk, increased productivity and revenue, appropriate adoption of technologies including improved education for practitioners, and improved outcomes for end users. Significant benefits will be demonstrated through the evaluations with practitioners in the areas of healthcare and energy.Read moreRead less
Information access through web-scale question-answer pair finding, ranking and matching. This project will aim to take web search to a new level of sophistication in accepting queries in the form of complex natural language questions, and returning a ranked list of natural language answers automatically extracted from a broad range of web user forums.