This study aims to explore potential reasons why the use of tools and methods corpus linguistics are not prevalent in English teaching Norway, using research question What do in-service teachers Norway find useful about corpora what they challenging? The provides interview data from teachers, contributing our understanding perspective on corpora. design consists seminars for (featuring LancsLex...

Collocations, i.e., recurrent word combinations such as take advantage (of), strong tea, and deeply absorbed, are receiving increasing attention in SLA research because of their importance to “native-like” production of language. Previous studies suggest that collocations pose a serious challenge to language learners and that learners’ L1 plays a crucial role in this respect. My paper aims to s...

We present results from a range of experiments on article and preposition error correction for non-native speakers of English. We first compare a language model and errorspecific classifiers (all trained on large English corpora) with respect to their performance in error detection and correction. We then combine the language model and the classifiers in a meta-classification approach by combin...

We present results from a range of experiments on article and preposition error correction for non-native speakers of English. We first compare a language model and errorspecific classifiers (all trained on large English corpora) with respect to their performance in error detection and correction. We then combine the language model and the classifiers in a meta-classification approach by combin...

We present a very simple model for text quality assessment based on a deep convolutional neural network, where the only supervision required is one corpus of usergenerated text of varying quality, and one contrasting text corpus of consistently high quality. Our model is able to provide local quality assessments in different parts of a text, which allows visual feedback about where potentially ...

Linguistic information is useful in natural language processing, information retrieval and a multitude of sub-tasks involving language analysis. Two types of linguistic information in all languages are part of speech and morphology. Part of speech information reflects syntactic structure and can assist in tasks such as speech recognition, machine translation and word sense disambiguation. Morph...

Transformation-based learning has been successfully employed to solve many natural language processing problems. It achieves state-of-the-art performance on many natural language processing tasks and does not overtrain easily. However, it does have a serious drawback: the training time is often intorelably long, especially on the large corpora which are often used in NLP. In this paper, we pres...

This work has been carried out in the context of automatic evaluation of learner summaries where text comprehension is gained using Latent Semantic Analysis (LSA) and Natural Language Processing (NLP) techniques. We had intuitively observed that lemmatized versions of LSA matrixes resembled better human Basque similarity judgement than the non lemmatized ones. This research was conducted to tes...

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...

Active learning techniques were employed for classification of dialogue acts over two dialogue corpora, the English humanhuman Switchboard corpus and the Spanish human-machine Dihana corpus. It is shown clearly that active learning improves on a baseline obtained through a passive learning approach to tagging the same data sets. An error reduction of 7% was obtained on Switchboard, while a fact...