Add to ORKGProceedings of the 17th Nordic Conference of Computational Linguistics NODALIDA 2009. Editors: Kristiina Jokinen and Eckhard Bick. NEALT Proceedings Series, Vol. 4 (2009), 227-230. © 2009 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio.no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle.net/10062/9206
We present an extensive experimental study of Phrase-based Statistical Machine Translation, from the...
<p>Machine translation has advanced considerably in recent years, primarily due to the availability ...
In the past few decades machine translation research has made major progress. A researcher now has a...
In data-driven Machine Translation approaches, like Example-Based Machine Translation (EBMT) (Brown...
Corpus based approaches to automatic translation such as Example Based and Statistical Machine Trans...
Statistical machine translation (SMT) mod-els need large bilingual corpora for train-ing, which are ...
Traditional active learning (AL) methods for machine translation (MT) rely on heuristics. However, t...
Translation needs have greatly increased during the last years. In many situations, text to be tran...
This paper investigates active learning to improve statistical machine translation (SMT) for low-res...
Interactive-predictive translation is a collaborative iterative process, where human translators pro...
Statistical Machine Translation (SMT) models learn how to translate by examining a bilingual paralle...
In recent years, corpus based approaches to machine translation have become predominant, with Statis...
Abstract The unavailability of parallel training corpora in resource-poor languages is a major bottl...
Machine translation is the application of machines to translate text or speech from one natural lang...
We explore how to improve machine translation systems by adding more translation data in situations ...
We present an extensive experimental study of Phrase-based Statistical Machine Translation, from the...
<p>Machine translation has advanced considerably in recent years, primarily due to the availability ...
In the past few decades machine translation research has made major progress. A researcher now has a...
In data-driven Machine Translation approaches, like Example-Based Machine Translation (EBMT) (Brown...
Corpus based approaches to automatic translation such as Example Based and Statistical Machine Trans...
Statistical machine translation (SMT) mod-els need large bilingual corpora for train-ing, which are ...
Traditional active learning (AL) methods for machine translation (MT) rely on heuristics. However, t...
Translation needs have greatly increased during the last years. In many situations, text to be tran...
This paper investigates active learning to improve statistical machine translation (SMT) for low-res...
Interactive-predictive translation is a collaborative iterative process, where human translators pro...
Statistical Machine Translation (SMT) models learn how to translate by examining a bilingual paralle...
In recent years, corpus based approaches to machine translation have become predominant, with Statis...
Abstract The unavailability of parallel training corpora in resource-poor languages is a major bottl...
Machine translation is the application of machines to translate text or speech from one natural lang...
We explore how to improve machine translation systems by adding more translation data in situations ...
We present an extensive experimental study of Phrase-based Statistical Machine Translation, from the...
<p>Machine translation has advanced considerably in recent years, primarily due to the availability ...
In the past few decades machine translation research has made major progress. A researcher now has a...