Articles

We present a method that improves data selection by combining a hybrid word/part-of-speech representation for corpora, with the idea of distinguishing between rare and frequent events. We validate our approach using data selection for machine translation, and show that it maintains or improves BLEU and TER translation scores while substantially …...

Translated texts (in any language) are so markedly different from original ones that text classification techniques can be used to tease them apart. Previous work has shown that awareness to these differences can significantly improve statistical ma- chine translation. These results, how- ever, required meta-information on the on- tological status …...

In this paper, the KIT systems submitted to the Shared Translation Task are presented. We participated in two translation direc- tions: from German to English and from English to German. Both translations are generated using phrase-based translation systems. The performance of the systems was boosted by using language models built …...

DFKI participated in the shared transla- tion task of WMT 2015 with the German- English language pair in each translation direction. The submissions were gener- ated using an experimental hybrid system based on three systems: a statistical Moses system, a commercial rule-based system, and a serial coupling of the two …...

This paper presents the results of the WMT15 shared tasks, which included a standard news translation task, a metrics task, a tuning task, a task for run-time estimation of machine translation quality, and an automatic post-editing task. This year, 68 machine translation systems from 24 institutions were submitted to the …...

This paper describes our WMT15 system submission for the translation task, a hy- brid system for English-to-Czech transla- tion. We repeat the successful setup from the previous two years. 1...

Identification of cognates is an important component of computer assisted second language learning systems. We present a simple rule-based system to recognize cognates in English text from the perspec- tive of the French language. At the core of our system is a novel similarity measure, orthographic edit distance, which incorpo- …...

One of the most common lexical transfor- mations between cognates in French and English is the presence or absence of a ter- minal “e”. However, many other transfor- mations exist, such as a vowel with a cir- cumflex corresponding to the vowel and the letter s. Our algorithms tested the …...

In this paper we describe an approach to automatic cognate identification in mono- lingual texts using machine translation. This system was used as our entry in the 2015 ALTA shared task, achieving an F1- score of 63% on the test set. Our pro- posed approach takes an input text in …...

Interpreting event mentions in text is cen- tral to many tasks from scientific research to intelligence gathering. We present an event trigger detection system and explore baseline configurations. Specifically, we test whether it is better to use a single multi-class classifier or separate binary classifiers for each label. The results …...

This paper presents an overview of the 6th ALTA shared task that ran in 2015. The task was to identify in English texts all the potential cognates from the per- spective of the French language. In other words, identify all the words in the Eng- lish text that would acceptably …...

Translation memories (TM) are widely used in the localization industry to im- prove consistency and speed of human translation. Several approaches have been presented to integrate the bilingual trans- lation units of TMs into statistical ma- chine translation (SMT). We present an extension of these approaches to the in- tegration …...

This paper presents experiments on the human ranking task performed during WMT2013. The goal of these experiments is to re-run the human evaluation task with translation studies students and to compare the results with the human rankings per- formed by the WMT development teams during WMT2013. More specifically, we test …...

The concept of fuzzy matching in trans- lation memories can take place using lin- guistically aware or unaware methods, or a combination of both. We designed a flexible and time-efficient framework which applies and combines linguistically unaware or aware metrics in the source and target language. We measure the correlation …...

This article presents a method of training maximum-entropy models to perform lexi- cal selection in a rule-based machine trans- lation system. The training method de- scribed is unsupervised; that is, it does not require any annotated corpus. The method uses source-language monolingual corpora, the machine translation (MT) system in which …...

This paper presents a method for cleaning and evaluating parallel corpora using word alignments and machine learning algorithms. It is based on the assumption that parallel sentences have many word alignments while non-parallel sentences have few or none. We show that it is possible to build an automatic classifier, which …...

We present a translation system that mod- els the selection of prepositions in a target- side generation component. This novel ap- proach allows the modeling of all subcate- gorized elements of a verb as either NPs or PPs according to target-side requirements relying on source and target side features. The …...

In this paper we analyse the use of pop- ular automatic machine translation evalu- ation metrics to provide labels for qual- ity estimation at document and paragraph levels. We highlight crucial limitations of such metrics for this task, mainly the fact that they disregard the discourse structure of the texts. …...

Multiple references in machine transla- tion evaluation are usually under-explored: they are ignored by alignment-based met- rics and treated as bags of n-grams in string matching evaluation metrics, none of which take full advantage of the recur- ring information in these references. By exploring information on the n-gram dis- tribution …...

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 …...