Milan Kundera et la littérature mondiale

« Les littératures nationales ne signifient plus grand-chose aujourd’hui. Nous entrons dans l’ère de la littérature mondiale et il appartient à chacun de nous de hâter cette évolution » (Goethe). Milan Kundera, écrivain natif de Moravie ayant émigré en France en 1975, reprend à son compte cet idéal formulé en 1827 par Goethe et le réactive : selon lui, en effet, le seul contexte où peuvent véritablement se révéler le sens et la valeur d’une œuvre est le grand contexte de l’histoire supranationale. Dans cet espace de diversité où l’œuvre n’est pas soutenue par son prestige national, mais par son originalité, un roman tchèque (littérature d’une petite nation) aussi bien qu’un roman français (littérature d’une grande nation) peut trouver sa place. Comment faire une histoire de la littérature mondiale sans la présenter comme une juxtaposition d’histoires littéraires nationales ? C’est la question à laquelle cette conférence s’efforcera de répondre en s’appuyant sur les réflexions culturelles aussi bien que politiques de Milan Kundera.

Complex syntax in autistic spectrum disorders: A study with relative clauses

Background The few studies that have evaluated syntax in autism spectrum disorder (ASD) have yielded conflicting findings: some suggest that once matched on mental age, ASD and typically developing controls do not differ for grammar, while others report that morphosyntactic deficits are independent of cognitive skills in ASD. There is a need for a better understanding of syntax in ASD and its relation to, or dissociation from, nonverbal abilities. Aims Syntax in ASD was assessed by evaluating subject and object relative clause comprehension in adolescents and adults diagnosed with ASD with a performance IQ within the normal range, and with or without a history of language delay. Methods & Procedures Twenty-eight participants with ASD (mean age 21.8) and 28 age-matched controls (mean age 22.07) were required to point to a character designated by relative clauses that varied in syntactic complexity. Outcomes & Results Scores indicate that participants with ASD regardless of the language development history perform significantly worse than age-matched controls with object relative clauses. In addition, participants with ASD with a history of language delay (diagnosed with high-functioning autism in the DSM-IV-TR) perform worse on subject relatives than ASD participants without language delay (diagnosed with Asperger syndrome in the DSM-IV-TR), suggesting that these two groups do not have equivalent linguistic abilities. Performance IQ has a positive impact on the success of the task for the population with ASD. Conclusions & Implications This study reveals subtle grammatical difficulties remaining in adult individuals with ASD within normal IQ range as compared with age-matched peers. Even in the absence of a history of language delay in childhood, the results suggest that a slight deficit may nevertheless be present and go undetected by standardized language assessments. Both groups with and without language delay have a similar global performance on relative clause comprehension; however, the study also indicates that the participants with reported language delay show more difficulty with subject relatives than the participants without language delay, suggesting the presence of differences in linguistic abilities between these subgroups of ASD.

A multifactorial analysis of explicitation in translation

The search for translation universals has been an important topic in translation studies over the past decades. In this paper, we focus on the notion of explicitation through a multifaceted study of causal connectives, integrating four different variables: the role of the source and the target languages, the influence of specific connectives and the role of the discourse relation they convey. Our results indicate that while source and target languages do not globally influence explicitation, specific connectives have a significant impact on this phenomenon. We also show that in English and French, the most frequently used connectives for explicitation share a similar semantic profile. Finally, we demonstrate that explicitation also varies across different discourse relations, even when they are conveyed by a single connective.

Using the Europarl corpus for linguistic research

Europarl is a large multilingual corpus containing the minutes of the debates at the European Parliament. This article presents a method to extract different corpora from Europarl: monolingual and multilingual comparable corpora, as well as parallel corpora. Using state-of-the-art measures of homogeneity, we show that these corpora are very similar. In addition, we argue that they present many advantages for research in various fields of linguistics and translation studies, and we also discuss some of their limitations. We conclude by reviewing a number of previous studies that made use of these corpora, emphasizing in each case the possibilities offered by Europarl.

Annotating discourse connectives by looking at their translation: The translation-spotting technique

The various meanings of discourse connectives like while and however are difficult to identify and annotate, even for trained human annotators. This problem is all the more important that connectives are salient textual markers of cohesion and need to be correctly interpreted for many NLP applications. In this paper, we suggest an alternative route to reach a reliable annotation of connectives, by making use of the information provided by their translation in large parallel corpora. This method thus replaces the difficult explicit reasoning involved in traditional sense annotation by an empirical clustering of the senses emerging from the translations. We argue that this method has the advantage of providing more reliable reference data than traditional sense annotation. In addition, its simplicity allows for the rapid constitution of large annotated datasets.

Automatic identification of discourse markers in dialogues: An in-depth study of like and well

The lexical items like and well can serve as discourse markers (DMs), but can also play numerous other roles, such as verb or adverb. Identifying the occurrences that function as DMs is an important step for language understanding by computers. In this study, automatic classifiers using lexical, prosodic/positional and sociolinguistic features are trained over transcribed dialogues, manually annotated with DM information. The resulting classifiers improve state-of-the-art performance of DM identification, at about 90% recall and 79% precision for like (84.5% accuracy, κ = 0.69), and 99% recall and 98% precision for well (97.5% accuracy, κ = 0.88). Automatic feature analysis shows that lexical collocations are the most reliable indicators, followed by prosodic/positional features, while sociolinguistic features are marginally useful for the identification of DM like and not useful for well. The differentiated processing of each type of DM improves classification accuracy, suggesting that these types should be treated individually.