Proceedings of the Seventh International Conference Formal Approaches to South Slavic and Balkan languages

Proceedings of the Seventh International Conference Formal Approaches to South Slavic and Balkan Languages publishes 17 papers that were presented at the conference organised in Dubrovnik, Croatia, 4-6 Octobre 2010

Corpus‐based analysis of spoken narratives. Introducing a corpus and a search tool

This paper is concerned with the development of a synchronic corpus containing Serbian spoken narratives and its use for narrative analysis. The corpus (CRONUS – Corpus for the Research On Narratives and their Use in Speech) is optimised to study the structure and use of this discourse genre. First, data sources are presented, followed by corpus creation and access. The semi-spontaneous spoken narratives were orthographically transcribed, and the corpus deeply annotated, with special emphasis on the annotation of narrative sections following Labov’s approach and the annotation of argument structure constructions in the sense of Construction Grammar. Three case studies demonstrate how morphological and constructional annotation can be effective for the exploration of narratives

FST Morphology for the Endangered Skolt Sami Language

Peer reviewe

Sociolinguistically Driven Approaches for Just Natural Language Processing

Natural language processing (NLP) systems are now ubiquitous. Yet the benefits of these language technologies do not accrue evenly to all users, and indeed they can be harmful; NLP systems reproduce stereotypes, prevent speakers of non-standard language varieties from participating fully in public discourse, and re-inscribe historical patterns of linguistic stigmatization and discrimination. How harms arise in NLP systems, and who is harmed by them, can only be understood at the intersection of work on NLP, fairness and justice in machine learning, and the relationships between language and social justice. In this thesis, we propose to address two questions at this intersection: i) How can we conceptualize harms arising from NLP systems?, and ii) How can we quantify such harms? We propose the following contributions. First, we contribute a model in order to collect the first large dataset of African American Language (AAL)-like social media text. We use the dataset to quantify the performance of two types of NLP systems, identifying disparities in model performance between Mainstream U.S. English (MUSE)- and AAL-like text. Turning to the landscape of bias in NLP more broadly, we then provide a critical survey of the emerging literature on bias in NLP and identify its limitations. Drawing on work across sociology, sociolinguistics, linguistic anthropology, social psychology, and education, we provide an account of the relationships between language and injustice, propose a taxonomy of harms arising from NLP systems grounded in those relationships, and propose a set of guiding research questions for work on bias in NLP. Finally, we adapt the measurement modeling framework from the quantitative social sciences to effectively evaluate approaches for quantifying bias in NLP systems. We conclude with a discussion of recent work on bias through the lens of style in NLP, raising a set of normative questions for future work

Selected proceedings of the 50th Linguistic Symposium on Romance Languages

Synopsis: The present volume presents a selection of the revised and peer-reviewed proceedings articles of the 50th Linguistic Symposium on Romance Languages (LSRL 50) which was hosted virtually by the faculty and students from the University of Texas at Austin. With contributions from rising and senior scholars from Europe and the Americas, the volume demonstrates the breadth of research in contemporary Romance linguistics with articles that apply corpus-based and laboratory methods, as well as theory, to explore the structure, use, and development of the Romance languages. The articles cover a wide range of fields including morphosyntax, semantics, language variation and change, sociophonetics, historical linguistics, language acquisition, and computational linguistics. In an introductory article, the editors document the sudden transition of LSRL 50 to a virtual format and acknowledge those who helped them to ensure the continuity of this annual scholarly meeting

Discourse analysis of arabic documents and application to automatic summarization

Dans un discours, les textes et les conversations ne sont pas seulement une juxtaposition de mots et de phrases. Ils sont plutôt organisés en une structure dans laquelle des unités de discours sont liées les unes aux autres de manière à assurer à la fois la cohérence et la cohésion du discours. La structure du discours a montré son utilité dans de nombreuses applications TALN, y compris la traduction automatique, la génération de texte et le résumé automatique. L'utilité du discours dans les applications TALN dépend principalement de la disponibilité d'un analyseur de discours performant. Pour aider à construire ces analyseurs et à améliorer leurs performances, plusieurs ressources ont été annotées manuellement par des informations de discours dans des différents cadres théoriques. La plupart des ressources disponibles sont en anglais. Récemment, plusieurs efforts ont été entrepris pour développer des ressources discursives pour d'autres langues telles que le chinois, l'allemand, le turc, l'espagnol et le hindi. Néanmoins, l'analyse de discours en arabe standard moderne (MSA) a reçu moins d'attention malgré le fait que MSA est une langue de plus de 422 millions de locuteurs dans 22 pays. Le sujet de thèse s'intègre dans le cadre du traitement automatique de la langue arabe, plus particulièrement, l'analyse de discours de textes arabes. Cette thèse a pour but d'étudier l'apport de l'analyse sémantique et discursive pour la génération de résumé automatique de documents en langue arabe. Pour atteindre cet objectif, nous proposons d'étudier la théorie de la représentation discursive segmentée (SDRT) qui propose un cadre logique pour la représentation sémantique de phrases ainsi qu'une représentation graphique de la structure du texte où les relations de discours sont de nature sémantique plutôt qu'intentionnelle. Cette théorie a été étudiée pour l'anglais, le français et l'allemand mais jamais pour la langue arabe. Notre objectif est alors d'adapter la SDRT à la spécificité de la langue arabe afin d'analyser sémantiquement un texte pour générer un résumé automatique. Nos principales contributions sont les suivantes : Une étude de la faisabilité de la construction d'une structure de discours récursive et complète de textes arabes. En particulier, nous proposons : Un schéma d'annotation qui couvre la totalité d'un texte arabe, dans lequel chaque constituant est lié à d'autres constituants. Un document est alors représenté par un graphe acyclique orienté qui capture les relations explicites et les relations implicites ainsi que des phénomènes de discours complexes, tels que l'attachement, la longue distance du discours pop-ups et les dépendances croisées. Une nouvelle hiérarchie des relations de discours. Nous étudions les relations rhétoriques d'un point de vue sémantique en se concentrant sur leurs effets sémantiques et non pas sur la façon dont elles sont déclenchées par des connecteurs de discours, qui sont souvent ambigües en arabe. o une analyse quantitative (en termes de connecteurs de discours, de fréquences de relations, de proportion de relations implicites, etc.) et une analyse qualitative (accord inter-annotateurs et analyse des erreurs) de la campagne d'annotation. Un outil d'analyse de discours où nous étudions à la fois la segmentation automatique de textes arabes en unités de discours minimales et l'identification automatique des relations explicites et implicites du discours. L'utilisation de notre outil pour résumer des textes arabes. Nous comparons la représentation de discours en graphes et en arbres pour la production de résumés.Within a discourse, texts and conversations are not just a juxtaposition of words and sentences. They are rather organized in a structure in which discourse units are related to each other so as to ensure both discourse coherence and cohesion. Discourse structure has shown to be useful in many NLP applications including machine translation, natural language generation and language technology in general. The usefulness of discourse in NLP applications mainly depends on the availability of powerful discourse parsers. To build such parsers and improve their performances, several resources have been manually annotated with discourse information within different theoretical frameworks. Most available resources are in English. Recently, several efforts have been undertaken to develop manually annotated discourse information for other languages such as Chinese, German, Turkish, Spanish and Hindi. Surprisingly, discourse processing in Modern Standard Arabic (MSA) has received less attention despite the fact that MSA is a language with more than 422 million speakers in 22 countries. Computational processing of Arabic language has received a great attention in the literature for over twenty years. Several resources and tools have been built to deal with Arabic non concatenative morphology and Arabic syntax going from shallow to deep parsing. However, the field is still very vacant at the layer of discourse. As far as we know, the sole effort towards Arabic discourse processing was done in the Leeds Arabic Discourse Treebank that extends the Penn Discourse TreeBank model to MSA. In this thesis, we propose to go beyond the annotation of explicit relations that link adjacent units, by completely specifying the semantic scope of each discourse relation, making transparent an interpretation of the text that takes into account the semantic effects of discourse relations. In particular, we propose the first effort towards a semantically driven approach of Arabic texts following the Segmented Discourse Representation Theory (SDRT). Our main contributions are: A study of the feasibility of building a recursive and complete discourse structures of Arabic texts. In particular, we propose: An annotation scheme for the full discourse coverage of Arabic texts, in which each constituent is linked to other constituents. A document is then represented by an oriented acyclic graph, which captures explicit and implicit relations as well as complex discourse phenomena, such as long-distance attachments, long-distance discourse pop-ups and crossed dependencies. A novel discourse relation hierarchy. We study the rhetorical relations from a semantic point of view by focusing on their effect on meaning and not on how they are lexically triggered by discourse connectives that are often ambiguous, especially in Arabic. A thorough quantitative analysis (in terms of discourse connectives, relation frequencies, proportion of implicit relations, etc.) and qualitative analysis (inter-annotator agreements and error analysis) of the annotation campaign. An automatic discourse parser where we investigate both automatic segmentation of Arabic texts into elementary discourse units and automatic identification of explicit and implicit Arabic discourse relations. An application of our discourse parser to Arabic text summarization. We compare tree-based vs. graph-based discourse representations for producing indicative summaries and show that the full discourse coverage of a document is definitively a plus