Exploiting Linguistic Data in Machine Translation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F09%3A00207410" target="_blank" >RIV/00216208:11320/09:00207410 - isvavai.cz</a>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Exploiting Linguistic Data in Machine Translation

Popis výsledku v původním jazyce

First, we examine methods for automatic extraction of verb valency dictionaries based on corpus data. We propose an automatic metric for estimating how much lexicographers' labour was saved and evaluate various frame extraction techniques using this metric. Second, we design and implement an MT system with transfer at various layers of language description, as defined in the framework of FGD. We primarily focus on the tectogrammatical (deep syntactic) layer. Third, we leave the framework of FGD and experiment with a rather direct, phrase-based MT system. Comparing various setups of the system and specifically treating target-side morphological coherence, we are able to significantly improve MT quality and out-perform a commercial MT system within a pre-defined text domain. The concluding chapter provides a broader perspective on the utility of lexicons in various applications, highlighting the successful features.

Název v anglickém jazyce

Exploiting Linguistic Data in Machine Translation

Popis výsledku anglicky

First, we examine methods for automatic extraction of verb valency dictionaries based on corpus data. We propose an automatic metric for estimating how much lexicographers' labour was saved and evaluate various frame extraction techniques using this metric. Second, we design and implement an MT system with transfer at various layers of language description, as defined in the framework of FGD. We primarily focus on the tectogrammatical (deep syntactic) layer. Third, we leave the framework of FGD and experiment with a rather direct, phrase-based MT system. Comparing various setups of the system and specifically treating target-side morphological coherence, we are able to significantly improve MT quality and out-perform a commercial MT system within a pre-defined text domain. The concluding chapter provides a broader perspective on the utility of lexicons in various applications, highlighting the successful features.

Druh

B - Odborná kniha

CEP obor

AI - Jazykověda

OECD FORD obor

—

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2009

Kód důvěrnosti údajů

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

ISBN

978-80-904175-8-8

Počet stran knihy

119

Název nakladatele

Institute of Formal and Applied Linguistics, Charles University

Místo vydání

—

Kód UT WoS knihy

—