Hybrid Architectures for Machine Translation Systems.
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| Title: | Hybrid Architectures for Machine Translation Systems. |
|---|---|
| Authors: | Thurmair, Gregor1 g.thurmair@linguatec.de |
| Source: | Language Resources & Evaluation. Feb2005, Vol. 39 Issue 1, p91-108. 18p. |
| Subjects: | Translators (Computer programs), Translating & interpreting, Language & languages, Computer software, Computer architecture |
| Abstract: | Although some progress has been made on the quality of Machine Translation in recent years, there is still a significant potential for quality improvement. There has also been a shift in paradigm of machine translation, from “classical” rule-based systems like METAL or LMT1 towards example-based or statistical MT.2 It seems to be time now to evaluate the progress and compare the results of these efforts, and draw conclusions for further improvements of MT quality. The paper starts with a comparison between statistical MT (henceforth: SMT) and rule-based MT (henceforth: RMT) systems, and describes the set-up and the evaluation results; the second section analyses the strengths and weaknesses of the respective approaches, and the third one discusses models of an architecture for a hybrid system. [ABSTRACT FROM AUTHOR] |
| Copyright of Language Resources & Evaluation is the property of Springer Nature 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 |
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| Header | DbId: egs DbLabel: Engineering Source An: 19148543 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Hybrid Architectures for Machine Translation Systems. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Thurmair%2C+Gregor%22">Thurmair, Gregor</searchLink><relatesTo>1</relatesTo><i> g.thurmair@linguatec.de</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Language+Resources+%26+Evaluation%22">Language Resources & Evaluation</searchLink>. Feb2005, Vol. 39 Issue 1, p91-108. 18p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Translators+%28Computer+programs%29%22">Translators (Computer programs)</searchLink><br /><searchLink fieldCode="DE" term="%22Translating+%26+interpreting%22">Translating & interpreting</searchLink><br /><searchLink fieldCode="DE" term="%22Language+%26+languages%22">Language & languages</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software%22">Computer software</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+architecture%22">Computer architecture</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Although some progress has been made on the quality of Machine Translation in recent years, there is still a significant potential for quality improvement. There has also been a shift in paradigm of machine translation, from “classical” rule-based systems like METAL or LMT1 towards example-based or statistical MT.2 It seems to be time now to evaluate the progress and compare the results of these efforts, and draw conclusions for further improvements of MT quality. The paper starts with a comparison between statistical MT (henceforth: SMT) and rule-based MT (henceforth: RMT) systems, and describes the set-up and the evaluation results; the second section analyses the strengths and weaknesses of the respective approaches, and the third one discusses models of an architecture for a hybrid system. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Language Resources & Evaluation is the property of Springer Nature 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=19148543 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10579-005-2698-z Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 91 Subjects: – SubjectFull: Translators (Computer programs) Type: general – SubjectFull: Translating & interpreting Type: general – SubjectFull: Language & languages Type: general – SubjectFull: Computer software Type: general – SubjectFull: Computer architecture Type: general Titles: – TitleFull: Hybrid Architectures for Machine Translation Systems. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Thurmair, Gregor IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2005 Type: published Y: 2005 Identifiers: – Type: issn-print Value: 1574020X Numbering: – Type: volume Value: 39 – Type: issue Value: 1 Titles: – TitleFull: Language Resources & Evaluation Type: main |
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