Articles

This paper demonstrates the possibility to make an existing automatic error classi- fier for machine translations independent from the requirement of lemmatisation. This makes it usable also for smaller and under-resourced languages and in situa- tions where there is no lemmatiser at hand. It is shown that cutting all words …...

In this paper the author presents meth- ods for dynamic terminology integration in statistical machine translation systems using a source text pre-processing work- flow. The workflow consists of exchange- able components for term identification, inflected form generation for terms, and term translation candidate ranking. Auto- matic evaluation for three language …...

In this paper we present an approach to re- duce data sparsity problems when translat- ing from morphologically rich languages into less inflected languages by selectively stemming certain word types. We de- velop and compare three different integra- tion strategies: replacing words with their stemmed form, combined input using al- …...

This paper presents the work done to port a deep-transfer rule-based machine trans- lation system to translate from a differ- ent source language by maximizing the ex- ploitation of existing resources and by lim- iting the development work. Specifically, we report the changes and effort required in each of the …...

This paper presents a machine transla- tion tool – based on Moses – developed for the International Maritime Organiza- tion (IMO) for the automatic translation of documents from Spanish, French, Rus- sian and Arabic to/from English. The main challenge lies in the insufficient size of in- house corpora (especially for …...

This paper describes the challenges of building a Statistical Machine Translation (SMT) system for non-fictional subtitles. Since our experiments focus on a “dif- ficult“ translation direction (i.e. French- German), we investigate several meth- ods to improve the translation perfor- mance. We also compare our in-house SMT systems (including domain adap- …...

The quality and quantity of articles in each Wikipedia language varies greatly. Trans- lating from another Wikipedia is a natural way to add more content, but the trans- lation process is not properly supported in the software used by Wikipedia. Past computer-assisted translation tools built for Wikipedia are not commonly …...

This paper presents a hybrid machine translation framework based on a pre- processor that translates fragments of the input text by using example-based ma- chine translation techniques. The pre- processor resembles a translation mem- ory with named-entity and chunk general- ization, and generates a high quality par- tial translation that …...

This paper aims at exploring the potential of a lay community as post-editors. It fo- cusses on 15 members of an online tech- nology support forum, native speakers of the target language (TL) and some knowl- edge of the source language (SL) trans- lating content that was machine translated from …...

The modelling of natural language tasks using data-driven methods is often hin- dered by the problem of insufficient nat- urally occurring examples of certain lin- guistic constructs. The task we address in this paper – quality estimation (QE) of machine translation – suffers from lack of negative examples at training …...

Statistical machine translation (SMT) suf- fers from various problems which are ex- acerbated where training data is in short supply. In this paper we address the data sparsity problem in the Farsi (Persian) lan- guage and introduce a new parallel cor- pus, TEP++. Compared to previous re- sults the new …...

We propose a novel dependency-based re- ordering model for hierarchical SMT that predicts the translation order of two types of pairs of constituents of the source tree: head-dependent and dependent-dependent. Our model uses the dependency struc- ture of the source sentence to capture the medium- and long-distance reorder- ings between …...

This paper investigates to what extent the use of paraphrasing in translation mem- ory (TM) matching and retrieval is use- ful for human translators. Current trans- lation memories lack semantic knowledge like paraphrasing in matching and re- trieval. Due to this, paraphrased seg- ments are often not retrieved. Lack of …...

This paper motivates the need for an ho- mogeneous way of measuring and estimat- ing translation effort (quality) in computer- aided translation. It then defines a general framework for the measurement and esti- mation of translation effort so that trans- lation technologies can be both optimized and combined in a …...

The increasing use of post-editing in localisation workflows has led to a great deal of research and development in the area, much of it requiring user evaluation. This paper compares some results from a post-editing user inter- face study carried out using novice and expert translator groups. By comparing rates …...

Discourse deixis is a linguistic phenomenon in which pronouns have verbal or clausal, rather than nominal, antecedents. Studies have esti- mated that between 5% and 10% of pronouns in non-conversational data are discourse deic- tic. However, current coreference resolution systems ignore this phenomenon. This paper presents an automatic system for …...

Readability depends on many factors rang- ing from shallow features like word length to semantic ones like coherence. We intro- duce novel graph-based coherence features based on frequent subgraphs and compare their ability to assess the readability of Wall Street Journal articles. In contrast to Pitler and Nenkova (2008) some …...

Most recent studies on coreference resolu- tion advocate accurate yet relatively com- plex models, relying on, for example, entity- mention or graph-based representations. As it has been convincingly demonstrated at the recent CoNLL 2012 shared task, such algo- rithms considerably outperform popular basic approaches, in particular mention-pair mod- els. This …...

We describe a semantic role labeler with state- of-the-art performance and low computational requirements, which uses convolutional and time-domain neural networks. The system is designed to work with features derived from a dependency parser output. Various system options and architectural details are discussed. Incremental experiments were run to explore the …...

This paper proposes a method of incremen- tally constructing semantic representations. Our method is based on Steedman’s Combina- tory Categorial Grammar (CCG), which has a transparent correspondence between the syn- tax and semantics. In our method, a derivation for a sentence is constructed in an incremen- tal fashion and the …...