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.
An intelligent machine modelling assistant for combinatorial optimisation. This project aims to discover key fundamental technologies for automating assistance to non-expert users in the formulation of mathematical models. Through automating the modelling of combinatorial optimization problems, this research will generate new knowledge to address the fundamental challenges of automatic mathematical modelling. This intelligent assistant will enable synthesis of new mathematical models through th ....An intelligent machine modelling assistant for combinatorial optimisation. This project aims to discover key fundamental technologies for automating assistance to non-expert users in the formulation of mathematical models. Through automating the modelling of combinatorial optimization problems, this research will generate new knowledge to address the fundamental challenges of automatic mathematical modelling. This intelligent assistant will enable synthesis of new mathematical models through the utilisation of pioneering natural language processing components and novel custom-made machine-readable knowledge bases. The outcome of this research will broaden access to high-quality models by non-expert workforce and alleviate the shortage of expert mathematicians, bringing significant social and economic benefits.Read moreRead less
Incremental syntactic parsing and coreference resolution. As computers become smaller, keyboards and screens become increasingly impractical. We'd like to be able to talk to our computers, but they'd have to understand what we say. This project will develop a computational model that tracks which things are talked about and identifies 'who did what to whom' in text or speech.
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
Computational models of synergies in human language acquisition. How do children learn language? Do they first learn to recognise words and then associate words with meanings, or do they use the meanings to figure out what the words are, or do they do both at the same time, and if so, how? This project will investigate questions like these using advanced computational models of the way children learn from their environment.
Spoken conversational search: contextual interactive techniques to support effective information search over a speech-only communication channel. This project will develop new techniques for effective information search using speech only, supporting improved information access for visually impaired people or in situations that require focused visual attention (e.g. driving). The techniques are based on a conversational approach to information search and presentation of results.
Talking about place: tapping human knowledge to enrich national spatial data sets. Place descriptions are a common way for people to describe a location, but no current tools are smart enough to understand them. Emergency call centres are risking lives, users of navigation or web services are frustrated and addressing these problems costs billions of dollars per year. This project comes with a novel, interdisciplinary approach to automatically interpret human place descriptions and will develop ....Talking about place: tapping human knowledge to enrich national spatial data sets. Place descriptions are a common way for people to describe a location, but no current tools are smart enough to understand them. Emergency call centres are risking lives, users of navigation or web services are frustrated and addressing these problems costs billions of dollars per year. This project comes with a novel, interdisciplinary approach to automatically interpret human place descriptions and will develop novel methods to capture placenames with their meaning for smarter databases and automatic interpretation procedures. This acquired knowledge will be an important step forward for Australia's data custodians and users. Australia's location information industry will gain a significant advantage on a highly competitive global market.Read moreRead less
Dialogue-to-Action:Towards A Self-Evolving Enterprise Intelligent Assistant. The project aims to develop a novel Self-Evolving Enterprise Intelligent Assistant (EIA) by leveraging the Chatbot-based dialogue technique to acquire information, infer user intentions, understand languages, and determine subsequent actions to take through Dialogue-to-Action modelling. This new generation EIA is equipped with Artificial Generalised Intelligence, with a broad skill set able to tackle multiple business t ....Dialogue-to-Action:Towards A Self-Evolving Enterprise Intelligent Assistant. The project aims to develop a novel Self-Evolving Enterprise Intelligent Assistant (EIA) by leveraging the Chatbot-based dialogue technique to acquire information, infer user intentions, understand languages, and determine subsequent actions to take through Dialogue-to-Action modelling. This new generation EIA is equipped with Artificial Generalised Intelligence, with a broad skill set able to tackle multiple business tasks and handle fast-changing scenarios in business. The Self-Evolving EIA is a critical step on the path towards the future generation of EIA. Expected outcomes of this project are to develop adaptive EIA for Small and Medium Enterprise to improve their customer service quality.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220100188
Funder
Australian Research Council
Funding Amount
$438,582.00
Summary
Generating Plots with Dialogue Based Executable Semantic Parsing. This project aims to address the limited abilities of dialogue systems by developing new models and data collection techniques. The project expects to address a major gap in Natural Language Processing using a model that generates computer code and updates it in response to user requests. Expected outcomes of this project include a system that interacts with a user in plain English to analyse data, and efficient methods of trainin ....Generating Plots with Dialogue Based Executable Semantic Parsing. This project aims to address the limited abilities of dialogue systems by developing new models and data collection techniques. The project expects to address a major gap in Natural Language Processing using a model that generates computer code and updates it in response to user requests. Expected outcomes of this project include a system that interacts with a user in plain English to analyse data, and efficient methods of training the system with minimal expert input. This should provide significant benefits to research and business by broadening the accessibility and efficiency of data analysis, enabling faster and wiser decisions.Read moreRead less
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.