D. Attanayake, Eckhard Pflügel, G. Hunter, J. Denholm-Price
{"title":"SWIMS (Speech-Based Web Interface for Mathematics Using Statistical Language Models): An Intelligent Editing Assistant for Mathematical Text","authors":"D. Attanayake, Eckhard Pflügel, G. Hunter, J. Denholm-Price","doi":"10.1109/IE.2012.41","DOIUrl":null,"url":null,"abstract":"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 user's 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.","PeriodicalId":156841,"journal":{"name":"2012 Eighth International Conference on Intelligent Environments","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Eighth International Conference on Intelligent Environments","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IE.2012.41","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
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 user's 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.