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Prediction is a central mechanism in the human language processing architecture. The psycholinguistic and neurolinguistic literature has seen a lively debate about what form prediction may take and what status it has for language processing in the human mind and brain. While predictions are a ubiquitous finding, the implications of these results for models of language processing differ. For instance, eyetracking data suggest that predictions may rely on sublexical orthographic information in natural reading, while electrophysiological data provide mixed evidence for form-based predictions during reading. Other research has revealed that humans rapidly adapt to text specifics and that their predictive capacity varies, broadly speaking, in accordance with inter- and intra-individual language proficiency, which cuts across the speaker groups (e.g. L1 vs. L2 speakers, skilled vs. untrained readers) traditionally used for experimental contrasts. There is therefore evidence that the kind and strength of linguistic predictions depend on (at least) three sources of variability in language processing: speaker, text genre and experimental method.
The aim of this Research Topic is to develop a better understanding of prediction in light of the three sources of variability in language processing, by providing an overview of state-of-the art research on predictive language processing and by bringing together research from various disciplines.
First, intra-and inter-individual differences and their influence on predictive processes remain underrepresented in experimental research on predictive processing. How do language users differ in their predictive abilities and strategies, and how are these differences shaped by e.g. biological, social and cultural factors?
Second, while language users experience great stylistic diversity in their daily language exposure and use, the majority of language processing research still focuses on a very constrained register of well-controlled sentences composed in the standard language. How are predictions shaped by extra- and meta-linguistic context, such as register/genre or accent/speaker identity, and how may this influence the processing of experimental items in another language or text variety?
Third, the Research Topic invites contributions that make use of a multi-method approach, such as combined behavioral and electrophysiological measures or experimental methods combined with measures extracted from corpus data. What opportunities and challenges do we face when integrating multiple approaches to examine linguistic, experimental and individual differences in human predictive capacity?
We welcome contributions from all areas of empirical psycho- and neurolinguistics, but contributions must explicitly address variability and variation in language and language processing. Relevant topics include individual differences and the impact of genre, modality, register and language variety. Contributions that go beyond single word and single sentence paradigms are especially desirable. Experimental, corpus-based, meta-analytic and review papers, as well as theoretical/opinion pieces are welcome; however, papers of the latter type should support their arguments with substantial empirical evidence from the literature. Particularly desirable are contributions which combine topics and/or methods, such as the impact of an individual's native dialect on processing of constructions that show variability in the standard language (e.g. choice of auxiliary, agreement of mass nouns, etc.) or experimental methods combined with measures extracted from corpus data such as information-theoretic surprisal.
Collaborative work in NFDI
(2023)
The non-profit association National Research Data Infrastructure (NFDI) promotes science and research through a National Research Data Infrastructure. Its aim is to develop and establish an overarching research data management (RDM) for Germany and to increase the efficiency of the entire German science system. After a two-and-a-half year build up phase, the process of adding new consortia, each representing a different data domain, has ended in March 2023. NFDI now has 26 disciplinary consortia (and one additional basic service collaboration). Now the full extent of cross-consortial interaction is beginning to show.
The Data Governance Act was proposed in late 2020 as part of the European Strategy for Data, and adopted on 30 May 2022 (as Regulation 2022/868). It will enter into application on 24 September 2023. The Data governance Act is a major development in the legal framework affecting CLARIN and the whole language community. With its new rules on the re-use of data held by the public sector bodies and on the provision of data sharing services, and especially its encouragement of data altruism, the Data Governance Act creates new opportunities and new challenges for CLARIN ERIC. This paper analyses the provisions of the Data Governance Act, and aims at initiating the debate on how they will impact CLARIN and the whole language community.
The landscape of digital lexical resources is often characterized by dedicated local portals and proprietary interfaces as primary access points for scholars and the interested public. In addition, legal and technical restrictions are potential issues that can make it difficult to efficiently query and use these valuable resources. As part of the research data consortium Text+, solutions for the storage and provision of digital language resources are being developed and provided in the context of the unified cross-domain German research data infrastructure NFDI. The specific topic of accessing lexical resources in a diverse and heterogenous landscape with a variety of participating institutions and established technical solutions is met with the development of the federated search and query framework LexFCS. The LexFCS extends the established CLARIN Federated Content Search that already allows accessing spatially distributed text corpora using a common specification of technical interfaces, data formats, and query languages. This paper describes the current state of development of the LexFCS, gives an insight into its technical details, and provides an outlook on its future development.
This White Paper sets out commonly agreed definitions on activities of consortia within NFDI. It aims to provide a common basis for reporting and reference regarding selected questions of cross-consortial relevance in DFG’s template for the Interim Reports. The questions were prioritised by an NFDI Task Force on Evaluation and Reporting (formerly Task Force Monitoring) as a result of discussing possible answers to the DFG template. In this process the need to agree on a generalizable meaning of terms commonly used in the context of NFDI, and reporting in particular, were identified from cross-consortial perspectives. Questions that showed the highest requirement on clarification are discussed in this White Paper. As NFDI evolves, the Task Force will likely propose further joint approaches for reporting in information infrastructures.
While each of broad relevance, the questions addressed relate to substantially different aspects of consortia’s work. They are thus also structured slightly different.
Als Teil der NFDI vernetzt Text+ ortsverteilt verschiedenste Daten und Dienste für die geisteswissenschaftliche Forschung und stellt sie der wissenschaftlichen Gemeinschaft FAIR zur Verfügung. In diesem Beitrag beschreiben wir die Umsetzung beispielhaft im Bereich der Text+ Datendomäne Sammlungen anhand von Korpora, die in verschiedenen Disziplinen Verwendung finden. Die Infrastruktur ist auf Erweiterbarkeit ausgelegt, so dass auch weitere Ressourcen über Text+ verfügbar gemacht werden können. Enthalten ist auch ein Ausblick auf weitere zu erwartende Entwicklungen. Ein Beitrag zur 9. Tagung des Verbands "Digital Humanities im deutschsprachigen Raum" - DHd 2023 Open Humanities Open Culture.