Discriminative reranking for context-sensitive spell-checker.
Nowadays, a large amount of documents is generated daily. These documents may contain some spelling errors which should be detected and corrected by using a proofreading tool. Therefore, the existence of automatic writing assistance tools such as spell-checkers/correctors could help to improve their...
| Publicado en: | Digital Scholarship in the Humanities Vol. 31; no. 2; pp. 411 - 428 |
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| Autores principales: | , |
| Formato: | Artículo |
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Oxford University Press / USA
6/1/2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=115711328&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 115711328 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 2055768X JEO9 jtl: Digital Scholarship in the Humanities issn: 2055768X maglogo: N pubinfo: dt: 6/1/2016 vid: 31 iid: 2 pid: 622 pub: Oxford University Press / USA artinfo: ui: 115711328 10.1093/llc/fqu062 ppf: 411 ppct: 17 formats: fmt: @attributes: type: P size: 683KB tig: atl: Discriminative reranking for context-sensitive spell-checker. aug: au: Mirzababaei, Behzad Faili, Heshaam affil: School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran Natural Language Processing Laboratory, School of Electrical and Computer Engineering, College of Engineering, Campus no. 2, North Kargar Ave. P. O. Box 14395/515, Tehran, Iran su: Spell checkers (Computer programs) Documentation Spelling errors Encyclopedias & dictionaries English language sug: subj: Spell checkers (Computer programs) Documentation Spelling errors Encyclopedias & dictionaries English language ab: Nowadays, a large amount of documents is generated daily. These documents may contain some spelling errors which should be detected and corrected by using a proofreading tool. Therefore, the existence of automatic writing assistance tools such as spell-checkers/correctors could help to improve their quality. Spelling errors could be categorized into five categories. One of them is real-word errors, which are misspelled words that have been wrongly converted into another word in the language. Detection of such errors requires discourse analysis rather than just checking the word in a dictionary. We propose a discourse-aware discriminative model to improve the results of context-sensitive spell-checkers by reranking their resulted n-best list. We augment the proposed reranker into two existing context-sensitive spell-checker systems; one of them is based on statistical machine translation and the other one is based on language model. We choose the keywords of the whole document as contextual features of the model and improve the results of both systems by employing the features in a log-linear reranker system. We evaluated the system on two different languages: English and Persian. The results of the experiments in English language on the Wall street journal test set show improvements of 4.5% and 5.2% in detection and correction recall, respectively, in comparison to the baseline method. The mentioned improvement on recall metric was achieved with comparable precision. We also achieve state-of-the-art performance on the Persian language. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: © 2019 EADH: The European Association for Digital Humanities. item: Digital Scholarship in the Humanities holder: Oxford University Press / USA dt: @attributes: year: 2016 holdings: @attributes: islocal: N |
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