English spelling and the computer

The first half of the book is about spelling, the second about computers. Chapter Two describes how English spelling came to be in the state that it’s in today. In Chapter Three I summarize the debate between those who propose radical change to the system and those who favour keeping it as it is, and I show how computerized correction can be seen as providing at least some of the benefits that have been claimed for spelling reform. Too much of the literature on computerized spellcheckers describes tests based on collections of artificially created errors; Chapter Four looks at the sorts of misspellings that people actually make, to see more clearly the problems that a spellchecker has to face. Chapter Five looks more closely at the errors that people make when they don’t know how to spell a word, and Chapter Six at the errors that people make when they know perfectly well how to spell a word but for some reason write or type something else. Chapter Seven begins the second part of the book with a description of the methods that have been devised over the last thirty years for getting computers to detect and correct spelling errors. Its conclusion is that spellcheckers have some way to go before they can do the job we would like them to do. Chapters Eight to Ten describe a spellchecker that I have designed which attempts to address some of the remaining problems, especially those presented by badly spelt text. In 1982, when I began this research, there were no spellcheckers that would do anything useful with a sentence such as, ‘You shud try to rember all ways to youz a lifejacket when yotting.’ That my spellchecker corrects this perfectly (which it does) is less impressive now, I have to admit, than it would have been then, simply because there are now a few spellcheckers on the market which do make a reasonable attempt at errors of that kind. My spellchecker does, however, handle some classes of errors that other spellcheckers do not perform well on, and Chapter Eleven concludes the book with the results of some comparative tests, a few reflections on my spellchecker’s shortcomings and some speculations on possible developments

Fifty years of spellchecking

A short history of spellchecking from the late 1950s to the present day, describing its development through dictionary lookup, affix stripping, correction, confusion sets, and edit distance to the use of gigantic databases

Ordering the suggestions of a spellchecker without using context.

Having located a misspelling, a spellchecker generally offers some suggestions for the intended word. Even without using context, a spellchecker can draw on various types of information in ordering its suggestions. A series of experiments is described, beginning with a basic corrector that implements a well-known algorithm for reversing single simple errors, and making successive enhancements to take account of substring matches, pronunciation, known error patterns, syllable structure and word frequency. The improvement in the ordering produced by each enhancement is measured on a large corpus of misspellings. The final version is tested on other corpora against a widely used commercial spellchecker and a research prototype

A large list of confusion sets for spellchecking assessed against a corpus of real-word errors

One of the methods that has been proposed for dealing with real-word errors (errors that occur when a correctly spelled word is substituted for the one intended) is the "confusion-set" approach - a confusion set being a small group of words that are likely to be confused with one another. Using a list of confusion sets drawn up in advance, a spellchecker, on finding one of these words in a text, can assess whether one of the other members of its set would be a better fit and, if it appears to be so, propose that word as a correction. Much of the research using this approach has suffered from two weaknesses. The first is the small number of confusion sets used. The second is that systems have largely been tested on artificial errors. In this paper we address these two weaknesses. We describe the creation of a realistically sized list of confusion sets, then the assembling of a corpus of real-word errors, and then we assess the potential of that list in relation to that corpus

Does the MS Spell Checker Effectively Correct Non-Native English Writers’ Errors? A Case Study of Saudi University Students

Those learning English as a second or foreign language use spell checkers to correct the mistakes and errors they may have made while typing texts on a computer However scholars have debated the effectiveness of such checkers which were originally designed to fix the spelling mistakes of native speakers An example of these checkers is the Microsoft MS Word program which constitutes the focus of the current study This study examined how MS Word treats misspellings made by Saudi learners of English as a foreign language It specifically addressed three research questions 1 which L2 spelling errors were successfully fixed by MS Word 2 which L2 spelling errors were unsuccessfully fixed by MS Word and 3 how did intermediate L2 learners respond to alternative corrections provided by MS Word A screentracking software Screencast-O-Matic was used to monitor the MS Word spell checker s treatment of misspelled words It was also used to track learners reactions to alternative corrections provided by MS Word in real time The study analysed 401 errors made by25 female intermediate-level English learners at a Saudi universit

Spellcheckers

Techniques of computer spellchecking from the 1950's to the 2000's

A compilation, tabulation and analysis of spelling errors made by pupils in grades four, five, and six in free writing of sentences using given stimuli words

Thesis (M.A.)--Boston Universit

A query-based SMS translation in information access system

Mobile technology has contributed to the evolution of several media of communication such as chats, emails and short message service (SMS) text. This has significantly influenced the traditional standard way of expressing views from letter writing to a high-tech form of expression known as texting language. In this paper we investigated building a mobile information access system based on SMS queries. The difficulties with SMS communication were explored in terms of the informal communication passage and the associated difficulty in searching and retrieving results from an SMS-based web search engine under its non-standardization. The query is a pre-defined phrase-based translated English version of the SMS. The SMS machine tool normalization algorithm (SCORE) was invented for the query to interface with the best ranked and highly optimized results in the search engine. Our results, when compared with a number of open sources SMS translators gave a better and robust performance of translation of the normalized SMS

Incorporating an error corpus into a spellchecker for Maltese

This paper discusses the ongoing development of a new Maltese spell checker, highlighting the methodologies which would best suit such a language. We thus discuss several previous attempts, highlighting what we believe to be their weakest point: a lack of attention to context. Two developments are of particular interest, both of which concern the availability of language resources relevant to spellchecking: (i) the Maltese Language Resource Server (MLRS) which now includes a representative corpus of c. 100M words extracted from diverse documents including the Maltese Legislation, press releases and extracts from Maltese web-pages and (ii) an extensive and detailed corpus of spelling errors that was collected whilst part of the MLRS texts were being prepared. We describe the structure of these resources as well as the experimental approaches focused on context that we are now in a position to adopt. We describe the framework within which a variety of different approaches to spellchecking and evaluation will be carried out, and briefly discuss the first baseline system we have implemented. We conclude the paper with a roadmap for future improvements.peer-reviewe