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Forgetting to deal with this type of errors in the texts poses a problem of understanding and ambiguity of the meaning of the sentence containing these errors. In this article, we propose a new approach to correct errors due to the insertion of space in a word, and at the same time correct other types of editing errors. This approach is based on the edit distance and uses bi-grams language models to correct words in context. The test conducted on hundreds of erroneous words (by insertion of space and/or by simple editing errors) made it possible to assess the relevance and validity of the methods developed to correct this type of error. 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data-doc_id="106877107" data-landing_url="https://www.academia.edu/108516188/Efficient_Weighted_Edit_Distance_and_N_gram_Language_Models_to_Improve_Spelling_Correction_of_Segmentation_Errors" data-login_uri="https://www.academia.edu/registrations/google_one_tap" data-moment_callback="onGoogleOneTapEvent" id="g_id_onload"></div><div class="ds-top-related-works--grid-container"><div class="ds-related-content--container ds-top-related-works--container"><h2 class="ds-related-content--heading">Related papers</h2><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="0" data-entity-id="24300569" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/24300569/Using_Part_of_Speech_and_Word_Sense_Disambiguation_for_Boosting_String_Edit_Distance_Spelling_Correction">Using Part-of-Speech and Word-Sense Disambiguation for Boosting String-Edit Distance Spelling Correction</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="46840552" href="https://hcuge.academia.edu/ChristianLovis">Christian Lovis</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Lecture Notes in Computer Science, 2001</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Using Part-of-Speech and Word-Sense Disambiguation for Boosting String-Edit Distance Spelling Correction","attachmentId":44635116,"attachmentType":"pdf","work_url":"https://www.academia.edu/24300569/Using_Part_of_Speech_and_Word_Sense_Disambiguation_for_Boosting_String_Edit_Distance_Spelling_Correction","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a 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ds2-5-body-xs">The International Arab Journal of Information Technology</p><p class="ds-related-work--abstract ds2-5-body-sm">Correcting spelling errors based on the context is a fairly significant problem in Natural Language Processing (NLP) applications. The majority of the work carried out to introduce the context into the process of spelling correction uses the n-gram language models. However, these models fail in several cases to give adequate probabilities for the suggested solutions of a misspelled word in a given context. To resolve this issue, we propose two new language models inspired by stochastic language models combined with edit distance. A first phase consists in finding the words of the lexicon orthographically close to the erroneous word and a second phase consists in ranking and limiting these suggestions. We have applied the new approach to Arabic language taking into account its specificity of having strong contextual connections between distant words in a sentence. To evaluate our approach, we have developed textual data processing applications, namely the extraction of distant transi...</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"New Language Models for Spelling Correction","attachmentId":113874481,"attachmentType":"pdf","work_url":"https://www.academia.edu/118190007/New_Language_Models_for_Spelling_Correction","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/118190007/New_Language_Models_for_Spelling_Correction"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="4254560" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/4254560/Correcting_real_word_spelling_errors_by_restoring_lexical_cohesion">Correcting real-word spelling errors by restoring lexical cohesion</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="4264010" href="https://javeriana.academia.edu/NestorAndres">Nestor Andres</a></div><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Correcting real-word spelling errors by restoring lexical cohesion","attachmentId":31732417,"attachmentType":"pdf","work_url":"https://www.academia.edu/4254560/Correcting_real_word_spelling_errors_by_restoring_lexical_cohesion","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/4254560/Correcting_real_word_spelling_errors_by_restoring_lexical_cohesion"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="3" data-entity-id="2687054" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/2687054/An_In_depth_Study_of_the_Automatic_Detection_and_Correction_of_Spelling_Mistakes">An In-depth Study of the Automatic Detection and Correction of Spelling Mistakes</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="35462" href="https://glasgow.academia.edu/IadhOunis">Iadh Ounis</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2005</p><p class="ds-related-work--abstract ds2-5-body-sm">ABSTRACT This paper discusses the issues involved in an information retrieval system when spelling errors are encountered in a query. We look at two classical algorithms that may be used to correct these errors and their consequent effect on the system's performance. The algorithms are the Levenshtein Distance and the Longest Common Subsequence. We experiment on a variety of test data and explore the impact of certain errors on an information retrieval system.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"An In-depth Study of the Automatic Detection and Correction of Spelling Mistakes","attachmentId":30680850,"attachmentType":"pdf","work_url":"https://www.academia.edu/2687054/An_In_depth_Study_of_the_Automatic_Detection_and_Correction_of_Spelling_Mistakes","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/2687054/An_In_depth_Study_of_the_Automatic_Detection_and_Correction_of_Spelling_Mistakes"><span 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Aouragh</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Journal of Computing and Digital Systems</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Global Spelling Correction in Context using Language Models: Application to the Arabic Language","attachmentId":98980779,"attachmentType":"pdf","work_url":"https://www.academia.edu/97330276/Global_Spelling_Correction_in_Context_using_Language_Models_Application_to_the_Arabic_Language","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/97330276/Global_Spelling_Correction_in_Context_using_Language_Models_Application_to_the_Arabic_Language"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="5" data-entity-id="30197878" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/30197878/Toward_filling_the_gap_between_interactive_and_fully_automatic_spelling_correction_using_the_linguistic_context">Toward filling the gap between interactive and fully-automatic spelling correction using the linguistic context</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="32541866" href="https://independent.academia.edu/PRuch">Patrick Ruch</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2001</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Toward filling the gap between interactive and fully-automatic spelling correction using the linguistic context","attachmentId":50656872,"attachmentType":"pdf","work_url":"https://www.academia.edu/30197878/Toward_filling_the_gap_between_interactive_and_fully_automatic_spelling_correction_using_the_linguistic_context","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/30197878/Toward_filling_the_gap_between_interactive_and_fully_automatic_spelling_correction_using_the_linguistic_context"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="6" data-entity-id="4064664" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/4064664/Four_types_of_context_for_automatic_spelling_correction">Four types of context for automatic spelling correction</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="3199073" href="https://ets.academia.edu/MichaelFlor">Michael Flor</a></div><p class="ds-related-work--metadata ds2-5-body-xs"> Traitement Automatique des Langues (TAL), 53:3, 61-99., 2012</p><p class="ds-related-work--abstract ds2-5-body-sm">Flor M. (2012). Four types of context for automatic spelling correction. Traitement Automatique des Langues (TAL), 53:3, 61-99. This paper presents an investigation on using four types of contextual information for improving the accuracy of automatic correction of single-token non-word misspellings. The task is framed as contextually-informed re-ranking of correction candidates. Immediate local context is captured by word n-grams statistics from a Web-scale language model. The second approach measures how well a candidate correction fits in the semantic fabric of the local lexical neighborhood, using a very large Distributional Semantic Model. In the third approach, recognizing a misspelling as an instance of a recurring word can be useful for reranking. The fourth approach looks at context beyond the text itself. If the approximate topic can be known in advance, spelling correction can be biased towards the topic. Effectiveness of proposed methods is demonstrated with an annotated corpus of 3,000 student essays from international high-stakes English language assessments. The paper also describes an implemented system that achieves high accuracy on this task."</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Four types of context for automatic spelling correction","attachmentId":31595726,"attachmentType":"pdf","work_url":"https://www.academia.edu/4064664/Four_types_of_context_for_automatic_spelling_correction","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/4064664/Four_types_of_context_for_automatic_spelling_correction"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="7" data-entity-id="68916975" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/68916975/A_Survey_of_Spelling_Error_Detection_and_Correction_Techniques">A Survey of Spelling Error Detection and Correction Techniques</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="193644425" href="https://independent.academia.edu/RitikaMishra34">Ritika Mishra</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2013</p><p class="ds-related-work--abstract ds2-5-body-sm">Spelling Correction is a process of detecting and sometimes providing suggestions for incorrectly spelled words in a text. Spell Checker is an application program that flags words in a document that may not be spelled correctly. Spell Checker may be stand-alone capable of operating on a block a text such as word processor, electronic dictionary. When some text is given as an input to spell checker, it list outs the incorrect words separately by checking their availability in the dictionary. Finally it provides the suggestions for the incorrect words from the dictionary. This survey paper covers almost all the spelling correction techniques. Keywords— Spell Checker, NLP, Error detection techniques, Error correction techniques.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A Survey of Spelling Error Detection and Correction Techniques","attachmentId":79218601,"attachmentType":"pdf","work_url":"https://www.academia.edu/68916975/A_Survey_of_Spelling_Error_Detection_and_Correction_Techniques","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/68916975/A_Survey_of_Spelling_Error_Detection_and_Correction_Techniques"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" 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