Language Pairs

AbstractIn this paper we give an overview of the 2007 evaluation campaign for the International Workshop on Spoken Language Translation (IWSLT)1. As with previous evaluation campaigns, the primary focus of …...

AbstractIn this paper, we present a simple protocol to evaluate word aligners on bilingual lexicon induction tasks from parallel corpora. Rather than resorting to gold standards, it relies on a …...

Models of word alignment built as sequences of links have limited expressive power, but are easy to decode. Word aligners that model the alignment matrix can express arbitrary align- ments, …...

While it is generally accepted that many trans- lation phenomena are correlated with linguis- tic structures, employing linguistic syntax for translation has proven a highly non-trivial task. The key assumption …...

We describe the Heidelberg University system for the Cross-lingual Textual Entailment task at SemEval-2012. The system relies on fea- tures extracted with statistical machine trans- lation methods and tools, combining …...

We present an approach which uses the sim- ilarity in semantic structure of bilingual par- allel sentences to bootstrap a pair of seman- tic role labeling (SRL) models. The setting …...

Parallel text is the fuel that drives modern machine translation systems. The Web is a comprehensive source of preexisting par- allel text, but crawling the entire web is impossible for …...

We describe TerrorCat, a submission to this year’s metrics shared task. It is a ma- chine learning-based metric that is trained on manual ranking data from WMT shared tasks 2008–2012. …...

In this study we compare two machine translation devices on twelve machine translation medical- domain specific tasks, and two transliteration tasks, altogether involving twelve language pairs, including English-Chinese and English-Russian, …...

This paper describes the UPC submissions to the WMT14 Metrics Shared Task: UPC- IPA and UPC-STOUT. These metrics use a collection of evaluation measures in- tegrated in ASIYA, a toolkit …...

We describe the Indiana University sys- tem for SemEval Task 5, the L2 writ- ing assistant task, as well as some exten- sions to the system that were completed after …...

We propose a method that learns a cross- lingual projection of word representations from one language into another. Our method utilizes translatable context pairs as bonus terms of the objective …...

Post-editing the output of a statistical machine translation (SMT) system to obtain high-quality translation has become an increasingly common application of SMT, which henceforth we re- fer to as post-editing-based …...

The existing machine translation systems, whether phrase-based or neural, have relied almost exclusively on word-level modelling with explicit segmentation. In this paper, we ask a fundamental question: can neural machine …...

This paper presents an study of the use of in- terlocking phrases in phrase-based statistical machine translation. We examine the effect on translation quality when the translation units used in …...

We describe and evaluate a simple method to extract parallel sentences from com- parable corpora. The approach, termed STACC, is based on expanded lexical sets and the Jaccard similarity coefficient. …...

We present in this paper the participation of the University of Hamburg in the Biomedical Translation Task of the Sec- ond Conference on Machine Translation (WMT 2017). Our contribution lies …...

AbstractRecent research in neural machine translation has largely focused on two aspects; neural network architectures and end-to-end learning algorithms. The problem of decoding, however, has received relatively little attention from …...

AbstractWhile Neural Machine Translation (NMT) technology has been around for a few years now in research and development, it is still in its infancy when it comes to customization readiness …...

AbstractRecent efforts in cross-lingual word embedding (CLWE) learning have predominantly focused on fully unsupervised approaches that project monolingual embeddings into a shared cross-lingual space without any cross-lingual signal. The lack …...

AbstractDespite the success of neural machine translation (NMT), simultaneous neural machine translation (SNMT), the task of translating in real time before a full sentence has been observed, remains challenging due …...

AbstractCode-mixing, the interleaving of two or more languages within a sentence or discourse is ubiquitous in multilingual societies. The lack of code-mixed training data is one of the major concerns …...

AbstractUnsupervised Bilingual Dictionary Induction methods based on the initialization and the self-learning have achieved great success in similar language pairs, e.g., English-Spanish. But they still fail and have an accuracy …...

AbstractCurrent approaches to machine translation (MT) either translate sentences in isolation, disregarding the context they appear in, or model context at the level of the full document, without a notion …...

AbstractWe report the results of the WMT20 shared task on Quality Estimation, where the challenge is to predict the quality of the output of neural machine translation systems at the …...

AbstractNeural machine translation (NMT) models usually suffer from catastrophic forgetting during continual training where the models tend to gradually forget previously learned knowledge and swing to fit the newly added …...

AbstractWe present InstaMap, an instance-based method for learning projection-based cross-lingual word embeddings. Unlike prior work, it deviates from learning a single global linear projection. InstaMap is a non-parametric model that …...

AbstractLanguage domains that require very careful use of terminology are abundant and reflect a significant part of the translation industry. In this work we introduce a benchmark for evaluating the …...

AbstractThis paper presents the submission of Huawei Translate Services Center (HW-TSC) to the WMT 2021 News Translation Shared Task. We participate in 7 language pairs, including Zh/En, De/En, Ja/En, Ha/En, …...

AbstractWord alignment, which aims to align translationally equivalent words between source and target sentences, plays an important role in many natural language processing tasks. Current unsupervised neural alignment methods focus …...

AbstractThis paper presents the NICT Kyoto submission for the WMT’21 Quality Estimation (QE) Critical Error Detection shared task (Task 3). Our approach relies mainly on QE model pretraining for which …...

AbstractMany works proposed methods to improve the performance of Neural Machine Translation (NMT) models in a domain/multi-domain adaptation scenario. However, an understanding of how NMT baselines represent text domain information …...

AbstractBilingual lexicons form a critical component of various natural language processing applications, including unsupervised and semisupervised machine translation and crosslingual information retrieval. In this work, we improve bilingual lexicon induction …...

AbstractThis paper presents a collection of parallel corpora generated by exploiting the COVID-19 related dataset of metadata created with the Europe Media Monitor (EMM) / Medical Information System (MediSys) processing …...

AbstractIn the seventh edition of the WMT Biomedical Task, we addressed a total of seven languagepairs, namely English/German, English/French, English/Spanish, English/Portuguese, English/Chinese, English/Russian, English/Italian. This year’s test sets covered three …...

AbstractThis paper reports the findings of the second edition of the Chat Translation Shared Task. Similarly to the previous WMT 2020 edition, the task consisted of translating bilingual customer support …...

AbstractWe present the results of the WMT’22 SharedTask on Large-Scale Machine Translation Evaluation for African Languages. The shared taskincluded both a data and a systems track, alongwith additional innovations, such …...

AbstractIn this paper, we describe our submission to the WMT22 metrics shared task. Our metric focuses on computing contextual and syntactic equivalences along with lexical, morphological, and semantic similarity. The …...

AbstractThis paper illustrates a new methodology based on Test Suites (Avramidis et al., 2018) with focus on Business Critical Errors (BCEs) (Stewart et al., 2022) to evaluate the output of …...