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Marchand (1969) claims that abbreviations and acronyms, which are also known as ‘initialisms’, are used to create “names of new scientific discoveries, trade-names, names of organizations, new foundations or offices, but occasionally, and chiefly in American English, personal and geographical names are also coined in this way” (Marchand, 1969: 452). However, initialisms that originate from netspeak, such as ‘LOL’, are different from the initialisms Marchand (1969) describes. These initialisms are not names of organizations or scientific discoveries; rather, they describe everyday things or phases. This kind of initialism is a new phenomenon that seemingly did not exist before the Internet, and the aim of this essay is thus to examine whether Internet has given us increased opportunities for this type of word formation. A corpus of informal English was created for this study and ten initialisms were extracted from that corpus. These initialisms were then examined in the Corpus of Contemporary American English. The data from the COCA showed that people do form and use this kind of initialism, albeit they do it very infrequently. Furthermore, the corpus data showed that these items are used in all different genres that exist in the COCA, except for academic writing. The data found in this study indicates that people seem create a new kind of initialism, and that people therefore have new opportunities to use this kind of word formation. However, the data is too sparse to draw any definite conclusions from it.

Online gaming is a relatively modern phenomenon that is not older than 20 years. Most online players speak English in some form, either by talking or writing. The two games, 'World of Warcraft' and 'Counterstrike' have taken over the gaming-world and the gamers' language has found its way right into the dictionary. The aim of the study was to examine how meanings of language change or evolve in the context of online video game playing. In this study, two gameplay videos were transcribed and analysed both qualitatively and quantitatively. Gaming words were identified through calculating word frequency in terms of types and tokens, and these identified words were then analysed qualitatively. The result contains three categories: Contextual Meaning, New Meaning, and New Words. The concepts of Contextual, New meaning and New Words were compared to dictionary meanings to see whether new meanings were created in the context of the gaming world. Based on the result, the study suggests that game language can influence the overall usage of language in the future.

Notre recherche se situe en lexicographie computationnelle, et concerne non seulement le support informatique aux ressources lexicales utiles pour la TA (traduction automatique) et la THAM (traduction humaine aidée par la machine), mais aussi l'architecture linguistique des bases lexicales supportant ces ressources, dans un contexte opérationnel (thèse CIFRE avec L&M).Nous commençons par une étude de l'évolution des idées, depuis l'informatisation des dictionnaires classiques jusqu'aux plates-formes de construction de vraies "bases lexicales" comme JIBIKI-1 [Mangeot, M. et al., 2003 ; Sérasset, G., 2004] et JIBIKI-2 [Zhang, Y. et al., 2014]. Le point de départ a été le système PIVAX-1 [Nguyen, H.-T. et al., 2007 ; Nguyen, H. T. & Boitet, C., 2009] de bases lexicales pour systèmes de TA hétérogènes à pivot lexical supportant plusieurs volumes par "espace lexical" naturel ou artificiel (UNL). En prenant en compte le contexte industriel, nous avons centré notre recherche sur certains problèmes, informatiques et lexicographiques.Pour passer à l'échelle, et pour profiter des nouvelles fonctionnalités permises par JIBIKI-2, dont les "liens riches", nous avons transformé PIVAX-1 en PIVAX-2, et réactivé le projet GBDLEX-UW++ commencé lors du projet ANR TRAOUIERO, en réimportant toutes les données (multilingues) supportées par PIVAX-1, et en les rendant disponibles sur un serveur ouvert.Partant d'un besoin de L&M concernant les acronymes, nous avons étendu la "macrostructure" de PIVAX en y intégrant des volumes de "prolexèmes", comme dans PROLEXBASE [Tran, M. & Maurel, D., 2006]. Nous montrons aussi comment l'étendre pour répondre à de nouveaux besoins, comme ceux du projet INNOVALANGUES. Enfin, nous avons créé un "intergiciel de lemmatisation", LEXTOH, qui permet d'appeler plusieurs analyseurs morphologiques ou lemmatiseurs, puis de fusionner et filtrer leurs résultats. Combiné à un nouvel outil de création de dictionnaires, CREATDICO, LEXTOH permet de construire à la volée un "mini-dictionnaire" correspondant à une phrase ou à un paragraphe d'un texte en cours de "post-édition" en ligne sous IMAG/SECTRA, ce qui réalise la fonctionnalité d'aide lexicale proactive prévue dans [Huynh, C.-P., 2010]. On pourra aussi l'utiliser pour créer des corpus parallèles "factorisés" pour construire des systèmes de TA en MOSES. / Our research is in computational lexicography, and concerns not only the computer support to lexical resources useful for MT (machine translation) and MAHT (Machine Aided Human Translation), but also the linguistic architecture of lexical databases supporting these resources in an operational context (CIFRE thesis with L&M).We begin with a study of the evolution of ideas in this area, since the computerization of classical dictionaries to platforms for building up true "lexical databases" such as JIBIKI-1 [Mangeot, M. et al., 2003 ; Sérasset, G., 2004] and JIBIKI-2 [Zhang, Y. et al., 2014]. The starting point was the PIVAX-1 system [Nguyen, H.-T. et al., 2007 ; Nguyen, H. T. & Boitet, C., 2009] designed for lexical bases for heterogeneous MT systems with a lexical pivot, able to support multiple volumes in each "lexical space", be it natural or artificial (as UNL). Considering the industrial context, we focused our research on some issues, in informatics and lexicography.To scale up, and to add some new features enabled by JIBIKI-2, such as the "rich links", we have transformed PIVAX-1 into PIVAX-2, and reactivated the GBDLEX-UW++ project that started during the ANR TRAOUIERO project, by re-importing all (multilingual) data supported by PIVAX-1, and making them available on an open server.Hence a need for L&M for acronyms, we expanded the "macrostructure" of PIVAX incorporating volumes of "prolexemes" as in PROLEXBASE [Tran, M. & Maurel, D., 2006]. We also show how to extend it to meet new needs such as those of the INNOVALANGUES project. Finally, we have created a "lemmatisation middleware", LEXTOH, which allows calling several morphological analyzers or lemmatizers and then to merge and filter their results. Combined with a new dictionary creation tool, CREATDICO, LEXTOH allows to build on the fly a "mini-dictionary" corresponding to a sentence or a paragraph of a text being "post-edited" online under IMAG/SECTRA, which performs the lexical proactive support functionality foreseen in [Huynh, C.-P., 2010]. It could also be used to create parallel corpora with the aim to build MOSES-based "factored MT systems".

To learn a language successfully, one needs to incorporate terms which are used commonly by native speakers but cannot be found in dictionaries. Words like uh-huh, oops, ouch, and brrr, are some examples of these terms. These expressions, commonly categorized under such linguistic labels as interjections (Ameka, 1992), alternants (Poyatos, 2002), and response cries (Goffman,1981), are what Dr. Lynn Henrichsen (1993) and Rebecca Oyer (1999) termed Unorthodox Oral Expressions (UOEs). These utterances are considered unorthodox because many of them are not formal or standard English words. Because of that, “we do not consider them part of the productive system of English,” so English dictionaries and textbooks rarely include these words (Luthy, 1983, p.19). Also, they are used mostly in informal speech rather than in formal written English. Hence, non-native English learners usually don’t have the opportunity to learn these informal utterances in English classes (Chittaladakorn, 2011; Oyer, 1999).Though unorthodox, these expressions are important for English language learners (ELL) to learn so that they will be able to carry out more natural and native-like conversations and understand what these utterances mean when native speakers use them. Because UOEs are so under-taught and there are so few teaching UOEs, there is a great need for a UOE dictionary that includes not only pronunciation and meaning, but also the syntactic features and semantic and pragmatic functions of these expressions. This project includes the creation of an online UOE dictionary to fill that need in English language acquisition.