Using TectoMT as a Preprocessing Tool for Phrase-Based Statistical Machine Translation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F10%3A10078045" target="_blank" >RIV/00216208:11320/10:10078045 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Using TectoMT as a Preprocessing Tool for Phrase-Based Statistical Machine Translation

Popis výsledku v původním jazyce

We present a systematic comparison of preprocessing techniques for two language pairs: English-Czech and English-Hindi. The two target languages, although both belonging to the Indo-European language family, show significant differences in morphology, syntax and word order. We describe how TectoMT, a successful framework for analysis and generation of language, can be used as preprocessor for a phrase-based MT system. We compare the two language pairs and the optimal sets of source-language transformations applied to them. The following transformations are examples of possible preprocessing steps: lemmatization; retokenization, compound splitting; removing/adding words lacking counterparts in the other language; phrase reordering to resemble the targetword order; marking syntactic functions. TectoMT, as well as all other tools and data sets we use, are freely available on the Web.

Název v anglickém jazyce

Using TectoMT as a Preprocessing Tool for Phrase-Based Statistical Machine Translation

Popis výsledku anglicky

We present a systematic comparison of preprocessing techniques for two language pairs: English-Czech and English-Hindi. The two target languages, although both belonging to the Indo-European language family, show significant differences in morphology, syntax and word order. We describe how TectoMT, a successful framework for analysis and generation of language, can be used as preprocessor for a phrase-based MT system. We compare the two language pairs and the optimal sets of source-language transformations applied to them. The following transformations are examples of possible preprocessing steps: lemmatization; retokenization, compound splitting; removing/adding words lacking counterparts in the other language; phrase reordering to resemble the targetword order; marking syntactic functions. TectoMT, as well as all other tools and data sets we use, are freely available on the Web.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

AI - Jazykověda

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2010

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Lecture Notes in Computer Science

ISSN

0302-9743

e-ISSN

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Svazek periodika

2010

Číslo periodika v rámci svazku

6231

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

8

Strana od-do

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Kód UT WoS článku

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EID výsledku v databázi Scopus

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