This paper presents the Dutch Parallel Corpus, a high-quality parallel corpus for Dutch, French and English consisting of more than ten million words. The corpus contains five different text types and is balanced with respect to text type and translation direction. All texts included in the corpus have been cleared from copyright. We discuss the importance of parallel corpora in various research domains and contrast the Dutch Parallel Corpus with existing parallel corpora. The Dutch Parallel Corpus distinguishes itself from other parallel corpora by having a balanced composition and by its availability to the wide research community, thanks to its copyright clearance. All texts in the corpus are sentence-aligned and further enriched with basic linguistic annotations (lemmas and word class information). Approximately 25,000 words of the Dutch-English part have been manually aligned at the sub-sentential level. Rich metadata facilitates the navigability of the corpus and enables users to select the texts that satisfy their needs. The entire corpus is released as full texts in XML format and is also available via a web interface, which supports basic and complex search queries and presents the results as parallel concordances. The corpus will be distributed by the Flemish-Dutch Human Language Technology Agency (TST-Centrale).Le présent article décrit un corpus parallèle de grande qualité en néerlandais, en français et en anglais contenant 10 millions de mots (DPC, pour Dutch Parallel Corpus). Les différents types textuels, au nombre de cinq, sont équilibrés, ainsi que les différentes directions de traduction. Tous les problèmes relatifs aux droits d’auteurs ont été résolus. L’importance de la disponibilité des corpus parallèles dans plusieurs domaines de recherche est discutée et nous comparons le DPC avec d’autres corpus multilingues actuels. Le DPC se distingue par sa composition équilibrée et par le fait qu’il est offert à l’ensemble des chercheurs, car il est libre de droits. Les textes sont alignés au niveau de la phrase et enrichis avec des annotations linguistiques (lemme, étiquettes morphologiques). De plus, environ 25 000 mots (dans la partie néerlandais-anglais) ont fait l’objet d’un alignement manuel sous-phrastique. La richesse des métadonnées permet d’effectuer un certain nombre de sélections adaptées aux besoins de l’utilisateur. L’exploitation se fait de deux manières : d’une part, il est possible d’accéder à l’intégralité du corpus et de s’en servir en format XML. D’autre part, le corpus est consultable à travers une interface web qui autorise des requêtes simples ou complexes et présente les résultats sous forme de concordances parallèles. Le corpus sera distribué par l’Agence néerlandaise et flamande pour le traitement automatique des langues (TST-Centrale)

Although there is pedagogical support for using computer adventure and role-playing games in order to learn a second language (L2), commercial games often lack the instructional qualities for making their language comprehensible for learners. In an interdisciplinary approach, this paper proposes a technique for adapting in-game text in order to teach L2 vocabulary, grounded in research on second language acquisition and adaptive learning systems.

Parallel corpora are a valuable resource for researchers across a wide range of disciplines, i.e. machine translation, computer-assisted translation, terminology extraction, computer-assisted language learning, contrastive linguistics and translation studies. Since the development of a high-quality parallel corpus is a time-consuming and costly process, the DPC project aimed at the creation of a multifunctional resource that satisfies the needs of this diverse group of disciplines.The resulting corpus-the Dutch Parallel Corpus (DPC)-is a ten-millionword, sentence-aligned, linguistically enriched parallel corpus for the language pairs Dutch-English and Dutch-French. As the DPC is bidirectional, the corpus can also be used as comparable corpus to study the differences between translated versus non-translated language. A small part of the corpus is trilingual. The DPC distinguishes itself from other parallel corpora by having a balanced composition (both in terms of text types and translation directions), by its availability to the wide research community thanks to its copyright clearance and by focusing on quality rather than quantity.

The aim of this paper is to illustrate the potential of a parallel corpus in the context of (computer-assisted) language learning. In order to do so, we propose to answer two main questions (1) what corpus (data) to use and (2) how to use the corpus (data). We provide an answer to the what-question by describing the importance and particularities of compiling and processing a corpus for pedagogical purposes. In order to answer the how-question, we first investigate the central concepts of the interactionist theory of second language acquisition: comprehensible input, input enhancement, comprehensible output and output enhancement. By means of two case studies, we illustrate how the abovementioned concepts can be realized in concrete corpus-based language learning activities. We propose a design for a receptive and productive language task and describe how a parallel corpus can be at the basis of powerful language learning activities. The Dutch Parallel Corpus, a ten-million word sentence aligned and annotated parallel corpus, is used to develop these language tasks