Romanian Language Technology — a view from an academic perspective

The article reports on research and developments pursued by the Research Institute for Artificial Intelligence "Mihai Draganescu" of the Romanian Academy in order to narrow the gaps identified by the deep analysis on the European languages made by Meta-Net white papers and published by Springer in 2012. Except English, all the European languages needed significant research and development in order to reach an adequate technological level, in line with the expectations and requirements of the knowledge society

How to match bilingual tweets ?

International audienceIn this paper, we propose a method that aligns comparable bilingual tweets which, not only takes into account the specificity of a Tweet, but treats also proper names, dates and numbers in two different languages. This permits to retrieve more relevant target tweets. The process of matching proper names between Arabic and English is a difficult task, because these two languages use different scripts. For that, we used an approach which projects the sounds of an English proper name into Arabic and aligns it with the most appropriate proper name. We evaluated the method with a classical measure and compared it to the one we developed. The experiments have been achieved on two parallel corpora and shows that our measure outperforms the baseline by 5.6% at R@1 recall

Cross-Dialectal Arabic Processing

International audienceWe present, in this paper an Arabic multi-dialect study including dialects from both the Maghreb and the Middle-east that we compare to the Modern Standard Arabic (MSA). Three dialects from Maghreb are concerned by this study: two from Algeria and one from Tunisia and two dialects from Middle-east (Syria and Palestine). The resources which have been built from scratch have lead to a collection of a multi-dialect parallel resource. Furthermore, this collection has been aligned by hand with a MSA corpus. We conducted several analytical studies in order to understand the relationship between these vernacular languages. For this, we studied the closeness between all the pairs of dialects and MSA in terms of Hellinger distance. We also performed an experiment of dialect identification. This experiment showed that neighbouring dialects as expected tend to be confused, making difficult their identification. Because the Arabic dialects are different from one region to another which make the communication between people difficult, we conducted cross-lingual machine translation between all the pairs of dialects and also with MSA. Several interesting conclusions have been carried out from this experiment

Terminology in Media Discourse: A Case Study of Terms Denoting Phobia Types in English, Lithuanian and Norwegian News Media Sites

The paper presents the trilingual (English – Lithuanian – Norwegian) analysis of the terms denoting phobia types in mass media discourse. The aim of the paper is threefold: to perform conceptual categorisation of the terms, establish the term formation patterns in the investigated languages, as well as to determine which phobia types were most often discussed in the selected news media sites (“The Guardian”, “DELFI” and “Dagbladet”) over a 10-year period. For the purposes of the research, a trilingual comparable corpus was compiled, from which 268 terms were manually extracted, matched and investigated. The findings of the research provide important information on conceptual, linguistic and social aspects of the phobia terms which may contribute to terminology research in the psychiatry domain

Creación de datos multilingües para diversos enfoques basados en corpus en el ámbito de la traducción y la interpretación

Accordingly, this research work aims at exploiting and developing new technologies and methods to better ascertain not only translators’ and interpreters’ needs, but also professionals’ and ordinary people’s on their daily tasks, such as corpora and terminology compilation and management. The main topics covered by this work relate to Computational Linguistics (CL), Natural Language Processing (NLP), Machine Translation (MT), Comparable Corpora, Distributional Similarity Measures (DSM), Terminology Extraction Tools (TET) and Terminology Management Tools (TMT). In particular, this work examines three main questions: 1) Is it possible to create a simpler and user-friendly comparable corpora compilation tool? 2) How to identify the most suitable TMT and TET for a given translation or interpreting task? 3) How to automatically assess and measure the internal degree of relatedness in comparable corpora? This work is composed of thirteen peer-reviewed scientific publications, which are included in Appendix A, while the methodology used and the results obtained in these studies are summarised in the main body of this document. Fecha de lectura de Tesis Doctoral: 22 de noviembre 2019Corpora are playing an increasingly important role in our multilingual society. High-quality parallel corpora are a preferred resource in the language engineering and the linguistics communities. Nevertheless, the lack of sufficient and up-to-date parallel corpora, especially for narrow domains and poorly-resourced languages is currently one of the major obstacles to further advancement across various areas like translation, language learning and, automatic and assisted translation. An alternative is the use of comparable corpora, which are easier and faster to compile. Corpora, in general, are extremely important for tasks like translation, extraction, inter-linguistic comparisons and discoveries or even to lexicographical resources. Its objectivity, reusability, multiplicity and applicability of uses, easy handling and quick access to large volume of data are just an example of their advantages over other types of limited resources like thesauri or dictionaries. By a way of example, new terms are coined on a daily basis and dictionaries cannot keep up with the rate of emergence of new terms