Learning Machine Translation
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| Title: | Learning Machine Translation |
|---|---|
| Description: | The Internet gives us access to a wealth of information in languages we don't understand. The investigation of automated or semi-automated approaches to translation has become a thriving research field with enormous commercial potential. This volume investigates how Machine Learning techniques can improve Statistical Machine Translation, currently at the forefront of research in the field. The book looks first at enabling technologies—technologies that solve problems that are not Machine Translation proper but are linked closely to the development of a Machine Translation system. These include the acquisition of bilingual sentence-aligned data from comparable corpora, automatic construction of multilingual name dictionaries, and word alignment. The book then presents new or improved statistical Machine Translation techniques, including a discriminative training framework for leveraging syntactic information, the use of semi-supervised and kernel-based learning methods, and the combination of multiple Machine Translation outputs in order to improve overall translation quality.ContributorsSrinivas Bangalore, Nicola Cancedda, Josep M. Crego, Marc Dymetman, Jakob Elming, George Foster, Jesús Giménez, Cyril Goutte, Nizar Habash, Gholamreza Haffari, Patrick Haffner, Hitoshi Isahara, Stephan Kanthak, Alexandre Klementiev, Gregor Leusch, Pierre Mahé, Lluís Màrquez, Evgeny Matusov, I. Dan Melamed, Ion Muslea, Hermann Ney, Bruno Pouliquen, Dan Roth, Anoop Sarkar, John Shawe-Taylor, Ralf Steinberger, Joseph Turian, Nicola Ueffing, Masao Utiyama, Zhuoran Wang, Benjamin Wellington, Kenji Yamada |
| Authors: | Cyril Goutte, Nicola Cancedda, Marc Dymetman, George Foster |
| Resource Type: | eBook. |
| Subjects: | Machine translating--Statistical methods |
| Categories: | COMPUTERS / Artificial Intelligence / General, COMPUTERS / Data Science / General |
| Database: | eBook Collection (EBSCOhost) |
| FullText | Links: – Type: ebook-pdf Text: Availability: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Learning Machine Translation – Name: Abstract Label: Description Group: Ab Data: The Internet gives us access to a wealth of information in languages we don't understand. The investigation of automated or semi-automated approaches to translation has become a thriving research field with enormous commercial potential. This volume investigates how Machine Learning techniques can improve Statistical Machine Translation, currently at the forefront of research in the field. The book looks first at enabling technologies—technologies that solve problems that are not Machine Translation proper but are linked closely to the development of a Machine Translation system. These include the acquisition of bilingual sentence-aligned data from comparable corpora, automatic construction of multilingual name dictionaries, and word alignment. The book then presents new or improved statistical Machine Translation techniques, including a discriminative training framework for leveraging syntactic information, the use of semi-supervised and kernel-based learning methods, and the combination of multiple Machine Translation outputs in order to improve overall translation quality.ContributorsSrinivas Bangalore, Nicola Cancedda, Josep M. Crego, Marc Dymetman, Jakob Elming, George Foster, Jesús Giménez, Cyril Goutte, Nizar Habash, Gholamreza Haffari, Patrick Haffner, Hitoshi Isahara, Stephan Kanthak, Alexandre Klementiev, Gregor Leusch, Pierre Mahé, Lluís Màrquez, Evgeny Matusov, I. Dan Melamed, Ion Muslea, Hermann Ney, Bruno Pouliquen, Dan Roth, Anoop Sarkar, John Shawe-Taylor, Ralf Steinberger, Joseph Turian, Nicola Ueffing, Masao Utiyama, Zhuoran Wang, Benjamin Wellington, Kenji Yamada – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Cyril+Goutte%22">Cyril Goutte</searchLink><br /><searchLink fieldCode="AR" term="%22Nicola+Cancedda%22">Nicola Cancedda</searchLink><br /><searchLink fieldCode="AR" term="%22Marc+Dymetman%22">Marc Dymetman</searchLink><br /><searchLink fieldCode="AR" term="%22George+Foster%22">George Foster</searchLink> – Name: TypePub Label: Resource Type Group: TypPub Data: eBook. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Machine+translating--Statistical+methods%22">Machine translating--Statistical methods</searchLink> – Name: SubjectBISAC Label: Categories Group: Su Data: <searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Artificial+Intelligence+%2F+General%22">COMPUTERS / Artificial Intelligence / General</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Data+Science+%2F+General%22">COMPUTERS / Data Science / General</searchLink> |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=nlebk&AN=259247 |
| RecordInfo | BibRecord: BibEntity: Classifications: – Code: 418.020285 Scheme: ddc Type: prePub Languages: – Code: eng Text: English Subjects: – SubjectFull: Machine translating--Statistical methods Type: general Titles: – TitleFull: Learning Machine Translation Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Cyril Goutte – PersonEntity: Name: NameFull: Nicola Cancedda – PersonEntity: Name: NameFull: Marc Dymetman – PersonEntity: Name: NameFull: George Foster – PersonEntity: Name: NameFull: Cyril Goutte – PersonEntity: Name: NameFull: Nicola Cancedda – PersonEntity: Name: NameFull: Marc Dymetman – PersonEntity: Name: NameFull: George Foster IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2009 – D: 04 M: 02 Type: profile Y: 2014 Identifiers: – Type: isbn-print Value: 9780262072977 – Type: isbn-electronic Value: 9780262255097 Titles: – TitleFull: Learning Machine Translation Type: main |
| ResultId | 1 |