Екітілді корпустар

Research in example-based machine translation (F,I~MT) has been hampered by the lack of efficient tree alignment al- gorithms for bilingual corpora. *ghis pa- per <lescribes an alignment algorithm for F,I~MT …...

Over the past decade or so, a lot of work in computational linguistics has been directed at finding ways to exploit the ever increasing volume of electronic bilingual corpora. These …...

Building a bilingual dictionary for transfer in a machine translation system is conventionally done by hand and is very time-consuming. In order to overcome this bottleneck, we propose a new …...

We propose a novel statistical translation model to improve translation selection of collocation. In the statistical approach that has been popularly applied for translation selection, bilingual corpora are used to …...

AbstractPre-processing of bilingual corpora plays an important role in Example-Based Machine Translation (EBMT) and Statistical-Based Machine Translation (SBMT). For our Mandarin-English EBMT system, pre-processing includes segmentation for Mandarin, bracketing for …...

When machine translation (MT) knowl- edge is automatically constructed from bilingual corpora, redundant rules are acquired due to translation variety. These rules increase ambiguity or cause incorrect MT results. To …...

We propose a completely unsupervised method for mining parallel sentences from quasi-comparable bilingual texts which have very different sizes, and which include both in-topic and off-topic documents. We discuss and …...

. In this paper, we present a language model based on clusters obtained by applying regular expressions to the training data and, thus, discriminating several different sentence types as, e.g. …...

. In statistical machine translation, word alignment models are trained on bilingual corpora. Long sentences pose severe problems: 1. the high computational requirements; 2. the poor quality of the resulting …...

We propose a method for compiling bi- lingual terminologies of multi-word terms (MWTs) for given translation pairs of seed terms. Traditional methods for bi- lingual terminology compilation exploit parallel texts, …...

Named Entity recognition (NER) is an im- portant part of many natural language pro- cessing tasks. Most current approaches employ machine learning techniques and require supervised data. However, many languages …...

. Based on large-scale bilingual corpora and the theories of vector space model and lexical mutual information, this paper explores the application of the traditional monolingual IR technology to converting …...

Named Entity recognition (NER) is an important part of many natural language processing tasks. Current approaches of- ten employ machine learning techniques and require supervised data. However, many languages lack …...

We introduce a word segmentation ap- proach to languages where word bound- aries are not orthographically marked, with application to Phrase-Based Statis- tical Machine Translation (PB-SMT). In- stead of using …...

This paper describes the development of French–English and English–French ma- chine translation systems for the 2010 WMT shared task evaluation. These sys- tems were standard phrase-based statisti- cal systems based …...

Integration of domain specific knowledge into a general purpose statistical machine translation (SMT) system poses challenges due to insufficient bilingual corpora. In this paper we propose a simplification-translation-restoration (STR) framework …...

Nowadays, there are large amounts of data available to train statistical machine trans- lation systems. However, it is not clear whether all the training data actually help or not. A …...

We present a framework, based on Sejane and Eger (2012), for inducing lexical semantic ty- pologies for groups of languages. Our frame- work rests on lexical semantic association net- works …...

AbstractThis paper describes the construction and usage of the MOR and GRASP programs for part of speech tagging and syntactic dependency analysis of the corpora in the CHILDES and TalkBank …...

In this paper we present our entry to the WMT’13 shared task: Quality Estima- tion (QE) for machine translation (MT). We participated in the 1.1, 1.2 and 1.3 sub-tasks with …...

The use of pivot languages and word- alignment techniques over bilingual cor- pora has proved an effective approach for extracting paraphrases of words and short phrases. However, inherent ambiguities in …...

This article reports on mass experiments sup- porting the idea that data extracted from strongly comparable corpora may successfully be used to build statistical machine translation systems of reasonable translation …...

Current machine translation systems require large bilingual corpora for training data. With large bilingual corpora, phrase-based and neural-based methods can achieve state-of-the-art performance. Nevertheless, such large bilingual corpora are unavailable …...

AbstractMultilingual Neural Machine Translation (MNMT) models are commonly trained on a joint set of bilingual corpora which is acutely English-centric (i.e. English either as source or target language). While direct …...

AbstractMachine translation (MT) requires a wide range of linguistic capabilities, which current end-to-end models are expected to learn implicitly by observing aligned sentences in bilingual corpora. In this work, we …...