Articles

This paper presents an unsupervised method for extracting parallel sentence pairs from a comparable corpus. A trans- lation system is used to mine the compa- rable corpus and to detect parallel sen- tence pairs. An iterative process is im- plemented not only to increase the num- ber of extracted parallel …...

The adequacy of inversion transduction grammars (ITGs) has been widely de- bated, and the discussion’s crux seems to be whether the search space is inclusive enough (Zens and Ney, 2003; Wellington et al., 2006; Søgaard and Wu, 2009). Parse failure rate when parses are constrained by word alignments is one …...

Example-Based Machine Translation (EBMT), like other corpus based methods, requires substantial parallel training data. One way to reduce data requirements and improve translation quality is to generalize parts of the parallel corpus into translation templates. This automated generalization process requires clustering. In most clustering approaches the optimal number of clusters …...

This paper describes the transfer compo- nent of a syntax-based Example-based Ma- chine Translation system. The source sen- tence parse tree is matched in a bottom-up fashion with the source language side of a parallel example treebank, which results in a target forest which is sent to the target language …...

We describe the effort of the Microsoft Translator team to develop a Haitian Cre- ole statistical machine translation engine from scratch in a matter of days. Haitian Creole presents a number of difficulties for devleoping an SMT system, princi- pal among these is the lack of significant amounts of parallel …...

We present a user case of the free/open- source Spanish ↔ Brazilian Portuguese Apertium machine translation system in- side the localization workflow of Au- todesk. This system, initially developed to perform general-domain translations, has been customized by Prompsit to fit with Autodesk needs and by respecting the lo- calization workflow …...

This paper introduces a new statistical pre- processing model for Rule-Based Machine Translation (RBMT) systems. We train a Statistical Machine Translation (SMT) system using monolingual corpora. This model can transform a source input to an RBMT system into a more target-language friendly or RBMT- system friendly “pivot” language. We apply …...

We present new results from a hybrid com- bination of rule-based machine translation (RBMT) with a variant of statistical ma- chine translation (SMT) that supports hier- archical structures and is therefore able to preserve more of the linguistic structures obtained from the RBMT system than ver- sions of SMT that …...

Weights of the various components in a standard Statistical Machine Translation model are usually estimated via Minimum Error Rate Training. With this, one finds their optimum value on a development set with the expectation that these opti- mal weights generalise well to other test sets. However, this is not always …...

The paper presents an exploratory study of the translation processes for 12 student and 12 professional translators. We re- late properties of the translators’ process data (eye movements and keystrokes) with the quality of the produced translations, using BLEU scores and human evalua- tion scores for fluency and accuracy to …...

This paper describes a rule-based machine translation system from Breton to French intended for producing gisting translations. The paper presents a summary of the ongo- ing development of the system, along with an evaluation of two versions, and some reflection on the use of MT systems for lesser-resourced or minority …...

Machine translation evaluation methods are highly necessary in order to analyze the performance of translation systems. Up to now, the most traditional methods are the use of automatic measures such as BLEU or the quality perception performed by na- tive human evaluations. In order to com- plement these traditional procedures, …...

This work investigates query translation using only Wikipedia-based resources in a two step approach: analysis and disam- biguation. After arguing that data mined from Wikipedia is particularly relevant to query translation, both from a lexical and a semantic perspective, we detail the im- plementation of the approach. In the analysis …...

Knowledge extraction from online reposito- ries such as PubMed holds the promise of dramatically speeding up biomedical research and drug design. After initially focusing on recognizing proteins and binary interactions, the community has recently shifted their at- tention to the more ambitious task of recogniz- ing complex, nested event structures. …...

With the increase in popularity of online re- view sites comes a corresponding need for tools capable of extracting the information most important to the user from the plain text data. Due to the diversity in products and ser- vices being reviewed, supervised methods are often not practical. We present …...

Opinion holder extraction is one of the impor- tant subtasks in sentiment analysis. The ef- fective detection of an opinion holder depends on the consideration of various cues on vari- ous levels of representation, though they are hard to formulate explicitly as features. In this work, we propose to use …...

In this paper, we present a dependency tree- based method for sentiment classification of Japanese and English subjective sentences us- ing conditional random fields with hidden variables. Subjective sentences often con- tain words which reverse the sentiment po- larities of other words. Therefore, interac- tions between words need to be …...

We examine the viability of building large polarity lexicons semi-automatically from the web. We begin by describing a graph propa- gation framework inspired by previous work on constructing polarity lexicons from lexi- cal graphs (Kim and Hovy, 2004; Hu and Liu, 2004; Esuli and Sabastiani, 2009; Blair- Goldensohn et al., …...

Factorization is the operation of transforming a production in a Linear Context-Free Rewrit- ing System (LCFRS) into two simpler produc- tions by factoring out a subset of the nontermi- nals on the production’s righthand side. Fac- torization lowers the rank of a production but may increase its fan-out. We show …...

Recently, relaxation approaches have been successfully used for MAP inference on NLP problems. In this work we show how to extend the relaxation approach to marginal inference used in conditional likelihood training, pos- terior decoding, confidence estimation, and other tasks. We evaluate our approach for the case of second-order dependency …...