spell checker research paper

Systematic review of spell-checkers for highly inflectional languages

• Published: 14 November 2019
• Volume 53 , pages 4051–4092, ( 2020 )

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• Shashank Singh 1 &
• Shailendra Singh 1  

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Performance of any word processor, search engine, social media relies heavily on the spell-checkers, grammar checkers etc. Spell-checkers are the language tools which break down the text to check the spelling errors. It cautions the user if there is any unintentional misspelling occurred in the text. In the area of spell-checking, we still lack an exhaustive study that covers aspects like strengths, limitations, handled errors, performance along with the evaluation parameters. In literature, spell-checkers for different languages are available and each one possesses similar characteristics however, have a different design. This study follows the guidelines of systematic literature review and applies it to the field of spell-checking. The steps of the systematic review are employed on 130 selected articles published in leading journals, premier conferences and workshops in the field of spell-checking of different inflectional languages. These steps include framing of the research questions, selection of research articles, inclusion/exclusion criteria and the extraction of the relevant information from the selected research articles. The literature about spell-checking is divided into key sub-areas according to the languages. Each sub-area is then described based on the technique being used. In this study, various articles are analyzed on certain criteria to reach the conclusion. This article suggests how the techniques from the other domains like morphology, part-of-speech, chunking, stemming, hash-table etc. can be used in development of spell-checkers. It also highlights the major challenges faced by researchers along with the future area of research in the field of spell-checking.

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• Artificial Intelligence

Abbreviations

Finite state machine

Dictionary lookup method

Morphological analysis

Edit distance

Minimum edit distance

Unicode splitting

Character-based longest short term memory

Soundex method

Levenstein edit distance

Confusion set

Reverse minimum edit distance

Direct dictionary lookup method

Edit distance method

Phonetic encoding method

Finite state representation

State table method

Finite state automata

Partition around medoid clustering

Double metaphone encoding

Word frequency

Sound and shape similarity

Reverse edit distance method

Tree-based algorithm

Parts of speech

Hidden Markov model

Graphical user interface

Finite state transition

Unknown word handling

Unknown proper noun handling

Application programming interface

Constituent word

Memory based language model

Finite state transition model

Dictionary approach

Canti check

Crowd sourcing

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Acknowledgements

The authors thank the reviewers for their insightful comments. The authors would also like to thank Ministry of Electronics and IT, Government of INDIA, for providing fellowship under Grant Number: PhD-MLA-4 (69)/2015-16 (Visvesvaraya PhD Scheme for Electronics and IT) to pursue Ph.D. work.

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Singh, S., Singh, S. Systematic review of spell-checkers for highly inflectional languages. Artif Intell Rev 53 , 4051–4092 (2020). https://doi.org/10.1007/s10462-019-09787-4

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• Talpur N Abdulkadir S Alhussian H Hasan M Aziz N Bamhdi A (2023) Deep Neuro-Fuzzy System application trends, challenges, and future perspectives: a systematic survey Artificial Intelligence Review 10.1007/s10462-022-10188-3 56 :2 (865-913) Online publication date: 1-Feb-2023 https://dl.acm.org/doi/10.1007/s10462-022-10188-3
• Buşe-Dragomir A Popescu P Mihăescu M (2021) Spell Checker Application Based on Levenshtein Automaton Intelligent Data Engineering and Automated Learning – IDEAL 2021 10.1007/978-3-030-91608-4_5 (45-53) Online publication date: 25-Nov-2021 https://dl.acm.org/doi/10.1007/978-3-030-91608-4_5

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Spell Checking Techniques in NLP: A Survey

• Nikhil Gupta , Pratistha Mathur
• Published 2012
• Computer Science, Linguistics

40 Citations

Survey of spell checking techniques for malayalam: nlp, design and implementation of hinspell -hindi spell checker using hybrid approach, study of spell checking techniques and available spell checkers in regional languages: a survey, spell checker for non word error detection: survey, a novel hybrid approach to detect and correct spelling in tamil text, spell checking and error correcting system for text paragraphs written in punjabi language using hybrid approach, design and implementation of online punjabi spell checker based on dynamic programming, frequency based spell checking and rule based grammar checking.

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A New Algorithm to Design and Implementation of Multilingual Spellchecker and Corrector

Sequence clustering algorithm for spell checking and spell suggestion in tamil language, 9 references, correcting spelling errors by modelling their causes, a technique for computer detection and correction of spelling errors, natural language processing and information retrieval, error pattern in bangla text, natural language processing and information retrieval, related papers.

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Accommodations Toolkit

Spell check: research.

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This fact sheet on spell check is part of the Accommodations Toolkit published by the National Center on Educational Outcomes (NCEO). It summarizes information and research findings on spell check as an accommodation [1] . This toolkit also contains a summary of states’ accessibility policies for spell check .

What is spell check? Spell check is a software feature that identifies possible misspellings, and either autocorrects or suggests possible corrections (Cullen et al, 2008; MacArthur, 1999). It is sometimes referred to as spell checker, spelling checker, spelling assistance. Spell check can help students correct spelling errors with less time focused on the writing mechanics of spelling which then allows them to concentrate more broadly on developing ideas or content in the writing process (MacArthur, 1999).

What are the research findings on who should use this accommodation? Spell check has been used for students with various disabilities in the elementary grades (Finch & Finch, 2013) and secondary grades (Finizio, 2008; Koretz & Hamilton, 2001). According to research findings, most of the students who receive this accommodation have specific learning disabilities (SLD) (Finizio, 2008; Koretz & Hamilton, 2001).

What are the research findings on implementation of spell check? No studies were identified on the implementation of spell check. Three studies examined the frequency of spell check.

• Two studies examined how frequently students received the spell check accommodation, and both found that spell check was one of the least frequently assigned accommodations at the elementary (Finch & Finch, 2013) and secondary (Koretz & Hamilton, 2001) levels.
• Finizio (2008) examined the match relationship between instructional accommodations and state assessment accommodations documented in the individualized education programs (IEPs) of secondary students with various disabilities, most of whom had SLD. The results indicated that spell checking was mostly used as an instructional accommodation and not generally used on assessments.

What perceptions do students and teachers have about spell check? No studies were found that examined student or teacher perceptions of spell check as an assessment accommodation.

What have we learned overall? Research studies found that spell check is one of least assigned assessment accommodations, though it may be used more often during instruction. It is used for elementary and secondary students with various disabilities, and is most frequently provided to students with SLD. No studies were identified that examined the effect of spell check on student performance. Research is needed on the effect of spell check on the performance of students with different disabilities, including English learners with disabilities. Likewise, there is a need to explore teacher and student perceptions of the spell check accommodation.

• Cullen, J., Richards, S., & Frank, C. L. (2008). Using software to enhance the writing skills of students with special needs . Journal of Special Education Technology , 23 (2), 33–44. https://doi.org/10.1177/016264340802300203
• Finch, W. H., & Finch, M. E. H. (2013). Differential item functioning analysis using a multilevel Rasch mixture model: Investigating the impact of disability status and receipt of testing accommodations . Journal of Applied Measurement , 15 (2), 133–151. http://jampress.org/
• Finizio, N. J., II. (2008). The relationship between instructional and assessment accommodations on student IEPs in a single urban school district (Publication No. 3313763) [Doctoral dissertation, University of Massachusetts Boston]. ProQuest Dissertations and Theses Global.
• Koretz, D., & Hamilton, L. (2001). The performance of students with disabilities on New York’s Revised Regents Comprehensive Examination in English (CSE Technical Report No. 540). Center for the Study of Evaluation (CRESST), UCLA. http://www.rand.org/content/dam/rand/pubs/drafts/2008/DRU2608.pdf
• MacArthur, C. A. (1999). Word prediction for students with severe spelling problems . Learning Disability Quarterly , 22 (3), 158–172. https://doi.org/10.2307/1511283

Attribution

All rights reserved. Any or all portions of this document may be reproduced and distributed without prior permission, provided the source is cited as:

• Goldstone, L., Lazarus, S. S., Hendrickson, K., Rogers, C., & Hinkle, A. R. (2022). Spell check: Research (NCEO Accommodations Toolkit #27a) . National Center on Educational Outcomes.

The Center is supported through a Cooperative Agreement (#H326G210002) with the Research to Practice Division, Office of Special Education Programs, U.S. Department of Education. The Center is affiliated with the Institute on Community Integration at the College of Education and Human Development, University of Minnesota. Consistent with EDGAR §75.62, the contents of this report were developed under the Cooperative Agreement from the U.S. Department of Education, but do not necessarily represent the policy or opinions of the U.S. Department of Education or Offices within it. Readers should not assume endorsement by the federal government. Project Officer: David Egnor

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