Learning Domain-Specific Transfer Rules: An Experiment with Korean to English Translation

Lavoie, Benoit; White, Michael; Korelsky, Tanya

doi:10.21236/ada457732

Cited by 3 publications

(4 citation statements)

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“…Both our system and transfer-based MT systems take a parse tree in the source language and translate it into a parse tree in the target language with transfer rules. There have been many recent proposals to acquire transfer rules automatically from word-aligned corpus (Carbonell et al 2002, Lavoie et al 2002, Richardson et al 2001. There are two main differences between our system and previous transfer-based approach: the unit of transfer and the generation module.…”

Section: Transfer-based Mtmentioning

confidence: 99%

A path-based transfer model for machine translation

Lin

2004

Proceedings of the 20th International Conference on Computational Linguistics - COLING '04

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We propose a path-based transfer model for machine translation. The model is trained with a word-aligned parallel corpus where the source language sentences are parsed. The training algorithm extracts a set of transfer rules and their probabilities from the training corpus. A rule translates a path in the source language dependency tree into a fragment in the target dependency tree. The problem of finding the most probable translation becomes a graph-theoretic problem of finding the minimum path covering of the source language dependency tree.

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Section: Transfer-based Mtmentioning

confidence: 99%

A path-based transfer model for machine translation

Lin

2004

Proceedings of the 20th International Conference on Computational Linguistics - COLING '04

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“…Some approached to have a machine translator learn domain-specific rules with various dictionaries [14]. On the other hand, Lee, Park, and Kim [15] tried to improve the accuracy of word selection in machine translation by using multiple knowledge sources including sense vectors, statistical context information, patterns, etc., and selecting the more appropriate target words.…”

Section: Introductionmentioning

confidence: 99%

Design of Knowledge-Based Communication between Human and Robot Using Ontological Semantic Technology in Firefighting Domain

Hong

Matson

Taylor

2014

Robot Intelligence Technology and Applications 2

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Abstract. This paper discusses how to design robot-human communication using Ontological Semantic Technology (OST), which is to address meanings of phrases or sentences in natural languages, in a firefighting domain. The OST is a system in an ontology-based structure to deal with different natural languages. In this study, English and Korean were selected to be implemented for the OST. The problem set is designed with Natural English, direct translation from the natural English to Korean, natural Korean, and direct translation from the natural Korean to English, which can be compared to examine the similarity of meanings with a language-independent ontology in processing English and Korean.

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“…Em dois dos métodos de indução de regras de tradução apresentados anteriormente - (Lavoie et al, 2002) e (Lavie et al, 2004) -essa métrica foi utilizada para avaliar o desempenho, como apresentado em detalhes na subseção 2.4.5.…”

Section: Avaliação Indireta Automáticaunclassified

“…Uma comparação dos valores obtidos na avaliação indireta das regras induzidas no Re-TraTos com os relatados na literatura para outros métodos de indução de regras de tradução, infelizmente, nãoé possível uma vez que nenhum dos métodos estudados aborda a indução de regras entre os pares pt-es e pt-en, e a maioria deles estuda idiomas muito diferentes, como nos pares coreano-inglês (Lavoie et al, 2002) ou inglês-turco (Öz & Cicekli, 1998).…”

Section: Dois Léxicos Bilíngües Foram Gerados Pelo Sistema Implementaunclassified

Indução de léxicos bilíngües e regras para a tradução automática

Caseli¹

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U S P -S ã o C a r l o s J u n h o d e 2 0 0 7Data da Defesa: 21/05/2007 Visto do Orientador: Agradecimentos Aos meus pais pelo grande amor que têm por mim e por serem meus grandes amigos. Ao meu irmão, minha outra metade, pela amizade e o exemplo de vida. Ao Leo, o amor da minha vida, por ser tudo aquilo o que sempre sonhei para um companheiro. As minhas grandes amigas que mesmoà distância continuam sempre presentes: Paula, Cadô, Patrícia, Lecy, Aninha e Karina. A Graça pelos anos de dedicação e orientação e por ter me guiado pela vida de pesquisadora. Ao Mikel pela orientação na Espanha. Aos colegas do NILC presentes e distantes que nestes 6 anos me ajudaram profissionalmente, em especial a Mônica, Carmen eÉlen. Aos amigos do NILC e, principalmente, ao trio AniAni, Thiago e Lê. Aos colegas da Espanha eàs minhas companheiras de piso Susana e Maloles. As professoras Carolina, Lúcia Rino, Sandra, Solange e Gladis pela atenção dispensada e pelos momentos de descontração. Aos professores da graduação Sérgio Schneider e Márcia Fernandes, grandes mestres e amigos. A FAPESP eà CAPES pelo apoio financeiro, ao NILC eà USP pelas instalações. As secretárias, aos porteiros,às faxineiras e aos amigos da cantina pela atenção e descontração do dia a dia. Enfim, a cada pessoa que nestes quatro anos cruzou o meu caminho me apoiando, me incentivando ou simplesmente me ouvindo ... muito obrigada! AbstractMachine Translation (MT) -the translation of a natural (source) language into another (target) by means of computer programs -is a hard task, mainly due to the need of deep linguistic knowledge about the two (or more) languages required to build resources such as translation grammars, bilingual dictionaries, etc. The scarcity of linguistic resources or even the difficulty to build them often limits the use of MT systems, for example, to certain application domains. In this context, several methods have been proposed aiming at generating linguistic knowledge automatically from multilingual resources, so that building translation tools becomes less hard. The ReTraTos project presented in this document is one of these proposals and aims at inducing translation lexicons and transfer rules automatically from PoS-tagged and lexically aligned translation examples for Portuguese-Spanish and Portuguese-English language pairs. The rule induction system brings forth a new approach, in which translation examples are split into alignment blocks and induction is performed for each type of block separately. Another new feature of this system is a more elaborate strategy for filtering the induced rules. Besides the translation lexicon and the transfer rule induction systems, we also implemented a MT module for validating the induced resources. The induced translation lexicons were evaluated intrinsically and the results obtained agree with those reported on the literature. The induced translation rules were evaluated directly and indirectly by the MT module, and improved the word-by-word translation in both directions (source-target and target-so...

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Learning Domain-Specific Transfer Rules: An Experiment with Korean to English Translation

Cited by 3 publications

References 6 publications

A path-based transfer model for machine translation

A path-based transfer model for machine translation

Design of Knowledge-Based Communication between Human and Robot Using Ontological Semantic Technology in Firefighting Domain

Indução de léxicos bilíngües e regras para a tradução automática

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