This paper presents a comparative study of spelling errors that are corrected as you type, vs. those that remain uncorrected. First, we generate naturally occurring online error correction data by logging users’ keystrokes, and by automatically deriving preand postcorrection strings from them. We then perform an analysis of this data against the errors that remain in the final text as well as a...

This research is a descriptive study in the survey model to determine direct and indirect effects between visual perception, phonological awareness, literacy errors. The design of exploratory correlational design. 552 first-grade primary school students participated study. data were collected using measurement tools named word-sentence writing/spelling, reading According findings, perception af...

Today the most accurate error correction techniques are statistical. But for low resourced languages like Urdu, where training error corpora are not available, statistical techniques are out of the question. Rule based techniques that exploit spelling error trends provide a useful alternative. The study of error patterns in a language is an essential prerequisite for designing such techniques. ...

To have a clearer idea of the problems students with dyslexia may face during their studies, we compared writings of 100 students with dyslexia and 100 age matched control students in higher education. The aim of this study was to compare the writing of young adults with dyslexia and young adults without dyslexia. The study was carried out in Belgium with writers of Dutch. First, we studied the...

We propose a spelling correction algorithm that combines trusted domain knowledge and query log information for query spelling correction. This algorithm uses query reformulations in the query log and bigram language models built from queries for efficiently and effectively generating correction suggestions and ranking them to find valid corrections. Experimental results show that for both simp...

One area in which artificial neural networks (ANNs) may strengthen NLP systems is in the identification of words under noisy conditions. In order to achieve this benefit when spelling errors or spelling variants are present, variable-length strings of symbols must be converted to ANN input/output form--fixed-length arrays of numbers. A common view in the neural network community has been that d...

Based on a corpus of 223 argumentative essays written by English as a foreign language learners, this study shows that spelling errors, whether detected manually or automatically, are a reliable predictor of the quality of L2 texts and that reliability is further improved by subcategorizing errors. However the benefit derived from subcategorization is much lower in the case of errors automatica...

There is a strong correlation between spelling errors and web text content quality. Using our lexical quality measure, based in a small corpus of spelling errors, we present an estimation of the lexical quality of the main Social Media sites. This paper presents an updated and complete analysis of the lexical quality of Social Media written in English and Spanish, including how lexical quality ...

Objectives: This research investigated three potential asymmetries in the production and perception of homophone spelling errors: aging, homophone dominance, and priming. A homophone spelling error occurs when a contextually appropriate word (beet) is replaced with its homophone (e.g., beat glaze). Two experiments investigated young and older adults' written production and detection of these er...