GLOSSER-RuG: in Support of Reading

Abstract

q'his paper reports ou ongoing work on a CAI,I, system to facilitate foreign lain guage learning: GI,()SSEI{-I{uG. The system is partieulm'ly dependent on advanc.ed morphological analysis, t!'ollowing a brief introduction to the project, the paper describes the architecture of GLOSSI';I{-RuG. Then wc describe iu detail the main compolmnts/modnles that are part of the implemented prototype. Finally, iml)lement,ation issues and details involving the user interfaces of the tool are discussed. We oul, line the design of an integrated system t,o SUl> port the reading of French text by ])ul, ctl speakers. 1 I n t r o d u c t i o n This paper reports on our ongoing research t,ow~rds a computer-assisted language learning (CALl,) tool, GLOSSI'2R-lhlG. After only several months, a first prototype was operational. This demonstrates that useful language-learning and language-assistance syste.ms are presently within reach given the availability of key components such ms morphological analysis software and online dict,ionaries. In the case of GLOSSF, tlA{uG, this was morphological analysis software made available by l{a, nk Xerox, Grenoble (Chanod and TN)anainen 1995; l)aniel Bauer and Zaenen 1995) and an online French-Dutch dictionary provided by Van Dale I,exicographie (Vanl)ale 1993). The system integrates previously existing soI'tware modules, and suptj ies the minimal additional ones together with interfaces in order to support the reading of French text by l)uteh speM~ers. Following a brief introduction to and motivation for the project, the paper describes the architecture of GLOSSI';R-I{uG. We describe the main component,s/modules (,hat arc. part of this pro retype, including implementat ion and the userinterface. 1.1. M o t i v a t i o n (Zaenen and Nunberg i995) notes that, (~ven as fully autontatic machine translation has receded a.s a reasonable mid-t,erm goal for natm'al language processing, several goals have emerged which are less ambitious, but LtSe['ul all(t att,ainable. These focus less on eliminating language loa.rriers and more on assisting peoI)h; in learning and understanding the wide. range of languages in current use. It, is still the. case t,hnt, language differences form a substantial barrier to the free [low of ideas and technologies: ideas are effec(,ively only a(-cessibh; only to l;hose in command of the la.nguagc they are (;xl)ressed in. But since an ever increasing number o[" people encounter t,ext,s electronically, au tomated methods of language processing may be brought to bear on this problem. (ILOSSERRuG is designed t,o hel t) peol)le who know a. bit of l!'rench but cannot read it; quickly or reliably. It allows a native Dutch pe.rson to learn more ahout, French morl)hology, it removes the tedious task of thumbing through the dictionary and it gives examples from corpora. (?,LOSSH{-IhK~ may also be contrasted with more t,radil,ional compute.r-assisted language learning (CALl,) sol'twarc (l,ast 1992) which has lbcused pr imary on providing exercises, answer keys, and links to g r ammar explanations. GI,OSSI~R-I{uG on the other hand, focuses ou l)roviding assistance to novice readers whether these are activeley involved in educational programs or not, and the locus is clearly on the level of word, including the grammat ica l information associated with intlectional endings. We therefore regard traditional CALl, software as complementary in purl)ose.

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Cite this paper

@inproceedings{Nerbonne1996GLOSSERRuGIS, title={GLOSSER-RuG: in Support of Reading}, author={John Nerbonne and Petra Smit}, booktitle={COLING}, year={1996} }