The emerging interdisciplinary field of Intelligent Computer Assisted Language Learning (ICALL) aims to integrate the knowledge from computational linguistics into computer-assisted language learning (CALL). REAP.PT is a project emerging from this new field, aiming to teach Portuguese in an innovative and appealing way, and adapted to each student. In this paper, we present a new improvement of...

This paper presents our preliminary work in developing a Natural Language Processing (NLP)-enhanced Computer-Assisted Language Learning (CALL) program for Japanese learners that supports reading comprehension and writing revision process with focus on zero anaphora. We first discuss the pedagogical status of zero anaphora in a Japanese as a Second Language (JSL) learning environment, and argue ...

For a long period, Computational Linguistics (CL) and Computer-Assisted Language Learning (CALL) have developed almost entirely independently of each other. A brief historical survey shows that the main reason for this state of affairs was the long preoccupation in CL with the general problem of Natural Language Understanding (NLU). As a consequence, much effort was directed to fields such as M...

We introduce a method for learning to predict text completion given a source text and partial translation. In our approach, predictions are offered aimed at alleviating users’ burden on lexical and grammar choices, and improving productivity. The method involves learning syntax-based phraseology and translation equivalents. At run-time, the source and its translation prefix are sliced into ngra...

In this article, we present a Computer Assisted Language Learning (CALL) environment for Basque. The environment has different aims: on the one hand, to offer the users (teachers, learners and computational linguists) different tools and language resources to clarify the linguistic doubts they might have about the language, and on the other hand, to store information about language learners, de...

We introduce a method for learning to predict the following grammar and text of the ongoing translation given a source text. In our approach, predictions are offered aimed at reducing users’ burden on lexical and grammar choices, and improving productivity. The method involves learning syntactic phraseology and translation equivalents. At run-time, the source and its translation prefix are slic...

1 Background and objectives of the project 1.1 Background The most prevalent forms of information technology in computer-assisted language learning (CALL) applications are email, multimedia and computerised multiple-choice test forms. Until recently, the contribution of language technology (LT) to CALL has been next to nonexistent, although there is now a growing amount of work in the LT commun...