The task of native language (L1) identification suffers from a relative paucity of useful training corpora, and standard within-corpus evaluation is often problematic due to topic bias. In this paper, we introduce a method for L1 identification in second language (L2) texts that relies only on much more plentiful L1 data, rather than the L2 texts that are traditionally used for training. In par...

In recent years, Bayesian models have become increasingly popular as a way of understanding human cognition. Ideal learner Bayesian models assume that cognition can be usefully understood as optimal behavior under uncertainty, a hypothesis that has been supported by a number of modeling studies across various domains (e.g., Griffiths & Tenenbaum, 2005; Xu & Tenenbaum, 2007). The models in these...

  This paper investigates the use of ‘lexical bundles’ in two broad corpora of journalistic writing. The aim of this study is to compare the use of lexical bundles in the two domains, one consisted of newspaper articles written in English and published in England and the other one comprised of newspaper articles written in Persian from Iranian publications. For this purpose, the frequency...

The impact of corpora is easily observable in Linguistics: it has changed the way we understand language use. However, despite their potential for impact in society, the use of corpora inside and outside the university settings in Northeast Brazil is still restricted. Rather than compiling another research corpus, the present project aims at engaging several educational communities in the use o...

Pattern-based approaches for Information Extraction typically apply a pattern learner to a set of domain-specific documents to generate extraction patterns that comprise the IE system. This limits the coverage of the system to the expressions and language constructs used within the training data. This research exploits the vast quantities of text readily available in large corpora, such as The ...

We test both bottom-up and top-down approaches in learning the phonemic status of the sounds of English and Japanese. We used large corpora of spontaneous speech to provide the learner with an input that models both the linguistic properties and statistical regularities of each language. We found both approaches to help discriminate between allophonic and phonemic contrasts with a high degree o...

Written and spoken data produced by learners has always been a key resource for the study of second language acquisition (SLA). However, for a long time the data used was rather artifi cial, i.e. resulting from highly controlled language tasks , and therefore not necessarily a refl ection of what learners do in more natural communication contexts. In addition, the data samples were usually quit...

Abstract Phonetic learner corpora represent a special type of spoken by providing detailed phonetic and phonological annotation in the form transcription as well segmentation labelling speech signal on levels segments, syllables, words sentences. This time-consuming post-processing enables better acoustic analysis data provides many options for using audio teaching foreign languages. It also of...