Monitoring English Sandhi Linking – A Study of Polish Listeners’ L2 Perception

This paper presents a set of word monitoring experiments with Polish learners of English. Listeners heard short recordings of native English speech, and were instructed to respond when they recognized an English target word that had been presented on a computer screen. Owing to phonological considerations, we compared reaction times to two types of vowel-initial words, which had been produced either with glottalization, or had been joined via sandhi linking processes to the preceding word. Results showed that the effects of the glottalization as a boundary cue were less robust than expected. Implications of these findings for models of L2 speech are discussed. It is suggested that the prevalence of glottalization in L1 production makes listeners less sensitive to its effects as a boundary cue in L2

Blog Style Classification: Refining Affective Blogs

In the constantly growing blogosphere with no restrictions on form or topic, a number of writing styles and genres have emerged. Recognition and classification of these styles has become significant for information processing with an aim to improve blog search or sentiment mining. One of the main issues in this field is detection of informative and affective articles. However, such differentiation does not suffice today. In this paper we extend the differentiation and suggest a fine-grained set of subcategories for affective articles. We propose and evaluate a classification method employing novel lexical, morphological, lightweight syntactic and structural features of written text. The results show that our method outperforms the existing approaches

KORPUSNI PRISTUP ENGLESKIM POSUĐENICAMA: BAZA ENGLESKIH RIJEČI U HRVATSKOME

Unadapted English loanwords have become part of informal communication in many languages, including Croatian. Their use is often motivated by the lack of adequate native equivalents, exposure to English through the media, but also by the prestigious status of the English language. A vast body of research has been dedicated to lexical borrowing, especially from English. At the same time, corpus analyses have mostly been conducted on smaller, ad hoc corpora. Therefore, the goal of this paper is to present the database of English loanwords in Croatian. The database was developed by algorithmic and manual classification of words from the Corpus of Croatian news portals, ENGRI, and provides a list of 9,452 unadapted English loanwords together with the data on their absolute and relative frequencies. The analysis showed that most loanwords (75.85%) appear less than 50 times, while a total of 44.78% of words appear 10 times or less. The biggest drop in the number of loanwords is observed in the categories of occurrence above 500, while only 27 words appear 5,000 times or more. The most frequent English loanword in the corpus is ‘show’ with 80,805 occurrences, which is 0.0122% of all words in the corpus. The analysis of loanwords that occur more than 5,000 times showed that most of them have Croatian translation equivalents, which confirms the role of the media in the introduction of new words. In addition to providing an insight into the occurrence of English loanwords in Croatian, this database also represents a valuable contribution to Croatian computational linguistics resources and enables future experimental research by providing the data on word frequency.Neprilagođene engleske posuđenice postale su dio neformalne komunikacije u mnogim jezicima, uključujući i hrvatski. Njihova je uporaba često motivirana nedostatkom odgovarajućih domaćih riječi, izloženošću engleskom jeziku kroz medije, ali i prestižnim statusom engleskog jezika. Jezično je posuđivanje česta tema jezikoslovnih istraživanja, posebice posuđivanje iz engleskog. Dosadašnji su rezultati uglavnom temeljeni na analizama manjih, ad hoc korpusa. Stoga je cilj ovoga rada predstaviti Bazu engleskih riječi u hrvatskome. Baza je nastala kao rezultat algoritamske i ručne klasifikacije posuđenica iz Korpusa novinskih portala ENGRI te donosi popis 9,452 neprilagođenih engleskih posuđenica i podatke o njihovoj pojavnosti u korpusu. Analiza dobivenih podataka pokazala je da se većina riječi (75,85%) pojavljuje manje od 50 puta, dok se ukupno 44,78% posuđenica pojavljuje 10 ili manje puta. Najveći pad u broju posuđenica primjećuje se u kategorijima pojavnosti iznad 500, dok se samo 27 posuđenica pojavljuje 5,000 puta ili više. Najčešća engleska posuđenica u navedenom korpusu je show, a pojavljuje se 80,805 puta, što je 0.0122% svih posuđenica u korpusu. Analiza posuđenica koje se pojavljuju više od 5,000 puta pokazala je da većina njih ima domaće prijevodne istovrijednice, što potvrđuje ulogu medija u uvođenju novih riječi. Osim što pruža uvid u pojavnost engleskih posuđenica u hrvatskome, ova baza predstavlja i doprinos hrvatskim računalno-jezikoslovnim resursima te omogućuje podatke potrebne za eksperimentalna istraživanja

Territory, Place, and Identity in Slovak Church-state Conflict: 1948-1989

This paper focuses on the development and utilization of a conceptual framework for studying religion from a spatial perspective, drawing on themes and methodologies from human geography. The goal of this research is to help reconnect the geography of religion as a subdiscipline with broader themes in the discipline. Through an examination of Catholicism in Slovakia between 1948 and 1989, it examines how the Church utilized and organized geographic space, how it crafted a Catholic sense of place, and how the Communist government in Slovakia competed with the Church for authority and control within these spatial 'realms.' Examining issues of territoriality, power relations, and identity formation at a number of spatial scales, ranging from the local to the international, the paper attempts to show their interrelation. This project draws on a collection of primary documents obtained from state and ecclesiastic archives in Eastern Slovakia

Transfer learning and subword sampling for asymmetric-resource one-to-many neural translation

There are several approaches for improving neural machine translation for low-resource languages: monolingual data can be exploited via pretraining or data augmentation; parallel corpora on related language pairs can be used via parameter sharing or transfer learning in multilingual models; subword segmentation and regularization techniques can be applied to ensure high coverage of the vocabulary. We review these approaches in the context of an asymmetric-resource one-to-many translation task, in which the pair of target languages are related, with one being a very low-resource and the other a higher-resource language. We test various methods on three artificially restricted translation tasks—English to Estonian (low-resource) and Finnish (high-resource), English to Slovak and Czech, English to Danish and Swedish—and one real-world task, Norwegian to North Sámi and Finnish. The experiments show positive effects especially for scheduled multi-task learning, denoising autoencoder, and subword sampling.There are several approaches for improving neural machine translation for low-resource languages: monolingual data can be exploited via pretraining or data augmentation; parallel corpora on related language pairs can be used via parameter sharing or transfer learning in multilingual models; subword segmentation and regularization techniques can be applied to ensure high coverage of the vocabulary. We review these approaches in the context of an asymmetric-resource one-to-many translation task, in which the pair of target languages are related, with one being a very low-resource and the other a higher-resource language. We test various methods on three artificially restricted translation tasks-English to Estonian (low-resource) and Finnish (high-resource), English to Slovak and Czech, English to Danish and Swedish-and one real-world task, Norwegian to North Sami and Finnish. The experiments show positive effects especially for scheduled multi-task learning, denoising autoencoder, and subword sampling.Peer reviewe

A survey on author profiling, deception, and irony detection for the Arabic language

"This is the peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."[EN] The possibility of knowing people traits on the basis of what they write is a field of growing interest named author profiling. To infer a user's gender, age, native language, language variety, or even when the user lies, simply by analyzing her texts, opens a wide range of possibilities from the point of view of security. In this paper, we review the state of the art about some of the main author profiling problems, as well as deception and irony detection, especially focusing on the Arabic language.Qatar National Research Fund, Grant/Award Number: NPRP 9-175-1-033Rosso, P.; Rangel-Pardo, FM.; Hernandez-Farias, DI.; Cagnina, L.; Zaghouani, W.; Charfi, A. (2018). 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