Articles

Long-distance reordering of syntactically divergent language pairs is a critical prob- lem. SMT has had limited success in han- dling these reorderings during inference, and thus deterministic preprocessing based on reordering parse trees is used. We con- sider German-to-English translation using Hiero. We show how to effectively model long-distance reorderings …...

The usefulness of a translated text for gist- ing purposes strongly depends on the over- all translation quality of the text, but espe- cially on the translation quality of the most informative portions of the text. In this paper we address the problems of rank- ing translated sentences within a …...

Many effective adaptation techniques for statistical machine translation crucially rely on in-domain development sets to learn model parameters. In this paper we present a novel method that automatically generates the matching tune set for Ara- bic-to-English MT with limited in- domain data1. This technique improves our MT system over two …...

We tackle the problem of domain adapta- tion of Statistical Machine Translation by exploiting domain-specific data acquired by domain-focused web-crawling. We de- sign and evaluate a procedure for auto- matic acquisition of monolingual and par- allel data and their exploitation for train- ing, tuning, and testing in a phrase-based Statistical …...

This paper presents a fast and accurate parallel sentence mining algorithm for comparable corpora called LEXACC based on the Cross-Language Infor- mation Retrieval framework combined with a trainable translation similarity measure that detects pairs of parallel and quasi-parallel sentences. LEXACC ob- tains state-of-the-art results in compari- son with established approaches. …...

Statistical-based methods are the preva- lent approaches for implementing machine translation systems today. However the resulted translations are usually flawed to some degree. We assume that a statisti- cal baseline system can be re-used to automatically learn how to (partially) correct translation errors, i.e. to turn a “broken” target translation …...

This paper reports a set of domain adap- tation techniques for improving Statisti- cal Machine Translation (SMT) for user- generated web forum content. We inves- tigate both normalization and supplemen- tary training data acquisition techniques, all guided by the aim of reducing the num- ber of Out-Of-Vocabulary (OOV) items in …...

In spite of much ongoing research on ma- chine translation evaluation there is little quantitative work that directly measures users’ intuitive or emotional preferences regarding different types of machine trans- lation errors. However, the elicitation and modeling of user preferences is an im- portant prerequisite for future research on user …...

Automatic post-editors (APEs) enable the re-use of black box machine translation (MT) systems for a variety of tasks where different aspects of translation are impor- tant. In this paper, we describe APEs that target adequacy errors, a critical problem for tasks such as cross-lingual question-answering, and compare different approaches for …...

We present an approach for translating subtitles where standard time and space constraints are modeled as part of the gen- eration of translations in a phrase-based statistical machine translation system (PB- SMT). We propose and experiment with two promising strategies for jointly trans- lating and compressing subtitles from En- glish …...

Software localization requires translating short text strings appearing in user inter- faces (UI) into several languages. These strings are usually unrelated to the other strings in the UI. Due to the lack of se- mantic context, many ambiguity problems cannot be solved during translation. How- ever, UI are composed of …...

This user study reports on an ongoing pilot that aims at using machine translation on a large scale, for the translation of technical documentation for a globally acting auto- motive supplier. The pilot is conducted by a language service provider and a research institution. First results go beyond expec- tations. …...

We present a set of free tools for building rule-based machine translation systems for polysynthetic languages. As there are no large corpora for most of the “small” lan- guages, it is often impossible to use sta- tistical methods. There are some free MT tools but very little work has been …...

We compare three methods of modeling morphological features in statistical ma- chine translation (SMT) from English to Arabic, a morphologically rich language. Features can be modeled as part of the core translation process mapping source tokens to target tokens. Alternatively these fea- tures can be generated using target mono- lingual …...

The performance of Phrase-Based Statis- tical Machine Translation (PBSMT) sys- tems mostly depends on training data. Many papers have investigated how to cre- ate new resources in order to increase the size of the training corpus in an at- tempt to improve PBSMT performance. In this work, we analyse and …...

We show in an empirical study that not only did all cross-lingual alternations of verb frames across Chinese–English trans- lations fall within the reordering capacity of Inversion Transduction Grammars, but more surprisingly, about 97% of the alter- nations were expressible by the far more restrictive Linear Transduction Grammars. Also, about …...

Enriching statistical models with linguis- tic knowledge has been a major concern in Machine Translation (MT). In mono- lingual data, adjuncts are optional con- stituents contributing secondarily to the meaning of a sentence. One can there- fore hypothesize that this secondary status is preserved in translation, and thus that adjuncts …...

We present a sub-sentential alignment al- gorithm that relies on association scores between words or phrases. This algorithm is inspired by previous work on alignment by recursive binary segmentation and on document clustering. We evaluate the re- sulting alignments on machine translation tasks and show that we can obtain state-of- …...

This work presents a HMT system for patent translation. The system exploits the high coverage of SMT and the high preci- sion of an RBMT system based on GF to deal with specific issues of the language. The translator is specifically developed to translate patents and it is evaluated in …...

This paper presents a novel approach to pivot-based machine translation (MT): while the state-of-the-art uses two statisti- cal systems, this proposal treats the second system as a black box. Our approach ef- fecively provides pivot-based MT to target languages for which no suitable bilingual corpora are available to build statistical …...