Discriminative reranking for context-sensitive spell-checker.
Saved in:
| Title: | Discriminative reranking for context-sensitive spell-checker. |
|---|---|
| Authors: | Mirzababaei, Behzad1,2, Faili, Heshaam1,2 hfaili@ut.ac.ir |
| Source: | Digital Scholarship in the Humanities. 6/1/2016, Vol. 31 Issue 2, p411-427. 17p. 10 Charts, 1 Graph. |
| Subjects: | Spell checkers (Computer programs), Documentation, Spelling errors, Encyclopedias & dictionaries, English language |
| Abstract: | 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. [ABSTRACT FROM AUTHOR] |
| Copyright of Digital Scholarship in the Humanities is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 115711328 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Discriminative reranking for context-sensitive spell-checker. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Mirzababaei%2C+Behzad%22">Mirzababaei, Behzad</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AR" term="%22Faili%2C+Heshaam%22">Faili, Heshaam</searchLink><relatesTo>1,2</relatesTo><i> hfaili@ut.ac.ir</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Digital+Scholarship+in+the+Humanities%22">Digital Scholarship in the Humanities</searchLink>. 6/1/2016, Vol. 31 Issue 2, p411-427. 17p. 10 Charts, 1 Graph. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Spell+checkers+%28Computer+programs%29%22">Spell checkers (Computer programs)</searchLink><br /><searchLink fieldCode="DE" term="%22Documentation%22">Documentation</searchLink><br /><searchLink fieldCode="DE" term="%22Spelling+errors%22">Spelling errors</searchLink><br /><searchLink fieldCode="DE" term="%22Encyclopedias+%26+dictionaries%22">Encyclopedias & dictionaries</searchLink><br /><searchLink fieldCode="DE" term="%22English+language%22">English language</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: 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. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Digital Scholarship in the Humanities is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=115711328 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1093/llc/fqu062 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 411 Subjects: – SubjectFull: Spell checkers (Computer programs) Type: general – SubjectFull: Documentation Type: general – SubjectFull: Spelling errors Type: general – SubjectFull: Encyclopedias & dictionaries Type: general – SubjectFull: English language Type: general Titles: – TitleFull: Discriminative reranking for context-sensitive spell-checker. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mirzababaei, Behzad – PersonEntity: Name: NameFull: Faili, Heshaam IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: 6/1/2016 Type: published Y: 2016 Identifiers: – Type: issn-print Value: 2055768X Numbering: – Type: volume Value: 31 – Type: issue Value: 2 Titles: – TitleFull: Digital Scholarship in the Humanities Type: main |
| ResultId | 1 |
