Dilaksha Attanayake

SWIMS (Speech-Based Web Interface for Mathematics Using Statistical Language Models): An Intelligent Editing Assistant for Mathematical Text

This paper describes the development and evaluation of an intelligent web-based interface for editing mathematical text that assists the user with the aid of the predictive and corrective power of statistical language models. It offers options for predicting what will appear next (analogous to predictive text for SMS messages) and identifying likely errors due to simple mistakes on the users part in order to assist in correcting the errors. Using text-stream input, we investigate the utility of the error identification by studying the proportion of times the correct version of the complete mathematical expression appears within the M most likely alternatives suggested by our system. We aim to integrate these facilities into our existing Talk Maths system.

Interactive error correction using statistical language models in a client-server interface for editing mathematical text

Learning and using mathematical notation poses particular difficulties for people with various disabilities, partly due to its wide range of symbols and rather complicated layout. These pose great challenges, often affecting the educational and career opportunities of people who are visually impaired or have limited (or no) use of their hands or arms. Assistive systems to alleviate these difficulties would be of considerable benefit to such groups of people