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Automatic Improvement Of Machine Translation Systems - Ariadna Font Llitjos
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ISBN: 9783639200447

Achieving high translation quality remains the most daunting challenge Machine Translation (MT) systems currently face. Researchers have explored a variety of methods for including translator feedback in the MT loop. However, most MT systems have failed to incorporate post-editing efforts beyond the addition of corrected translations to the parallel training data for Example-Based and Statistical systems or to a translation memory database. This book describes a novel approach that utilizes post-editing information to automatically improve the underlying rules and lexical entries of a Transfer-Based MT system. This approach directly improves the intelligibility of corrected MT output and, more significantly, it generalizes over unseen data, providing improved MT output for similar sentences that have not been corrected. Experimental results on an English-Spanish MT system show that automatic rule refinements triggered by bilingual speaker corrections successfully translate unseen data that was incorrectly translated by the original, unrefined grammar. Besides MT researchers, this work should be especially useful to anyone seeking to use or implement high quality MT. Books Books ~~ Computers~~ Information Technology Automatic-Improvement-Of-Machine-Translation-Systems~~Ariadna-Font-Llitjos VDM Verlag Achieving high translation quality remains the most daunting challenge Machine Translation (MT) systems currently face. Researchers have explored a variety of methods for including translator feedback in the MT loop. However, most MT systems have failed to incorporate post-editing efforts beyond the addition of corrected translations to the parallel training data for Example-Based and Statistical systems or to a translation memory database. This book describes a novel approach that utilizes post-editing information to automatically improve the underlying rules and lexical entries of a Transfer-Based MT system. This approach directly improves the intelligibility of corrected MT output and, more significantly, it generalizes over unseen data, providing improved MT output for similar sentences that have not been corrected. Experimental results on an English-Spanish MT system show that automatic rule refinements triggered by bilingual speaker corrections successfully translate unseen data that was incorrectly translated by the original, unrefined grammar. Besides MT researchers, this work should be especially useful to anyone seeking to use or implement high quality MT.

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Automatic Improvement of Machine Translation Systems - Ariadna Font Llitjós
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recycling non-expert user feedback Achieving high translation quality remains the most daunting challenge Machine Translation (MT) systems currently face. Researchers have explored a variety of methods for including translator feedback in the MT loop. However, most MT systems have failed to incorporate post-editing efforts beyond the addition of corrected translations to the parallel training data for Example-Based and Statistical systems or to a translation memory database. This book describes a novel approach that utilizes post-editing information to automatically improve the underlying rules and lexical entries of a Transfer-Based MT system. This approach directly improves the intelligibility of corrected MT output and, more significantly, it generalizes over unseen data, providing improved MT output for similar sentences that have not been corrected. Experimental results on an English-Spanish MT system show that automatic rule refinements triggered by bilingual speaker corrections successfully translate unseen data that was incorrectly translated by the original, unrefined grammar. Besides MT researchers, this work should be especially useful to anyone seeking to use or implement high quality MT. Bücher / Fremdsprachige Bücher / Englische Bücher 978-3-639-20044-7, VDM Verlag Dr. Müller e.K.

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Automatic Improvement of Machine Translation Systems - Ariadna Font Llitjós
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Achieving high translation quality remains the most daunting challenge Machine Translation (MT) systems currently face. Researchers have explored a variety of methods for including translator feedback in the MT loop. However, most MT systems have failed to incorporate post-editing efforts beyond the addition of corrected translations to the parallel training data for Example-Based and Statistical systems or to a translation memory database. This book describes a novel approach that utilizes post-editing information to automatically improve the underlying rules and lexical entries of a Transfer-Based MT system. This approach directly improves the intelligibility of corrected MT output and, more significantly, it generalizes over unseen data, providing improved MT output for similar sentences that have not been corrected. Experimental results on an English-Spanish MT system show that automatic rule refinements triggered by bilingual speaker corrections successfully translate unseen data that was incorrectly translated by the original, unrefined grammar. Besides MT researchers, this work should be especially useful to anyone seeking to use or implement high quality MT. recycling non-expert user feedback Buch (fremdspr.) Bücher>Fremdsprachige Bücher>Englische Bücher, VDM Verlag Dr. Müller e.K.

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Automatic Improvement of Machine Translation Systems - recycling non-expert user feedback - Taschenbuch

2009, ISBN: 9783639200447

[ED: Taschenbuch / Paperback], [PU: VDM Verlag Dr. Müller], Achieving high translation quality remains the most daunting challenge Machine Translation (MT) systems currently face. Researchers have explored a variety of methods for including translator feedback in the MT loop. However, most MT systems have failed to incorporate post-editing efforts beyond the addition of corrected translations to the parallel training data for Example-Based and Statistical systems or to a translation memory database. This book describes a novel approach that utilizes post-editing information to automatically improve the underlying rules and lexical entries of a Transfer-Based MT system. This approach directly improves the intelligibility of corrected MT output and, more significantly, it generalizes over unseen data, providing improved MT output for similar sentences that have not been corrected. Experimental results on an English-Spanish MT system show that automatic rule refinements triggered by bilingual speaker corrections successfully translate unseen data that was incorrectly translated by the original, unrefined grammar. Besides MT researchers, this work should be especially useful to anyone seeking to use or implement high quality MT., [SC: 0.00], Neuware, gewerbliches Angebot, 220 mm, [GW: 270g]

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Automatic Improvement of Machine Translation Systems - Ariadna Font Llitjós
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Ariadna Font Llitjós:
Automatic Improvement of Machine Translation Systems - neues Buch

ISBN: 9783639200447

ID: 471459737

Achieving high translation quality remains the most daunting challenge Machine Translation (MT) systems currently face. Researchers have explored a variety of methods for including translator feedback in the MT loop. However, most MT systems have failed to incorporate post-editing efforts beyond the addition of corrected translations to the parallel training data for Example-Based and Statistical systems or to a translation memory database. This book describes a novel approach that utilizes post-editing information to automatically improve the underlying rules and lexical entries of a Transfer-Based MT system. This approach directly improves the intelligibility of corrected MT output and, more significantly, it generalizes over unseen data, providing improved MT output for similar sentences that have not been corrected. Experimental results on an English-Spanish MT system show that automatic rule refinements triggered by bilingual speaker corrections successfully translate unseen data that was incorrectly translated by the original, unrefined grammar. Besides MT researchers, this work should be especially useful to anyone seeking to use or implement high quality MT. recycling non-expert user feedback Buch (fremdspr.) Bücher>Fremdsprachige Bücher>Englische Bücher, [PU: VDM Verlag Dr. Müller, Saarbrücken]

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Automatic Improvement of Machine Translation Systems
Autor:

Font Llitjós, Ariadna

Titel:

Automatic Improvement of Machine Translation Systems

ISBN-Nummer:

9783639200447

Achieving high translation quality remains the most daunting challenge Machine Translation (MT) systems currently face. Researchers have explored a variety of methods for including translator feedback in the MT loop. However, most MT systems have failed to incorporate post-editing efforts beyond the addition of corrected translations to the parallel training data for Example-Based and Statistical systems or to a translation memory database. This book describes a novel approach that utilizes post-editing information to automatically improve the underlying rules and lexical entries of a Transfer-Based MT system. This approach directly improves the intelligibility of corrected MT output and, more significantly, it generalizes over unseen data, providing improved MT output for similar sentences that have not been corrected. Experimental results on an English-Spanish MT system show that automatic rule refinements triggered by bilingual speaker corrections successfully translate unseen data that was incorrectly translated by the original, unrefined grammar. Besides MT researchers, this work should be especially useful to anyone seeking to use or implement high quality MT.

Detailangaben zum Buch - Automatic Improvement of Machine Translation Systems


EAN (ISBN-13): 9783639200447
ISBN (ISBN-10): 3639200446
Taschenbuch
Erscheinungsjahr: 2009
Herausgeber: VDM Verlag
196 Seiten
Gewicht: 0,308 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 18.06.2010 15:57:11
Buch zuletzt gefunden am 01.10.2016 23:22:05
ISBN/EAN: 9783639200447

ISBN - alternative Schreibweisen:
3-639-20044-6, 978-3-639-20044-7

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