After successful previous conferences in the UK, New Zealand, the United States, Australia and Denmark, the 6th Variation and Language Processing Conference (VALP6) will be held at Universidade de Vigo from 26-28 June 2024.
In its first edition, at the University of Chester (UK) in 2011, this conference was designed to bring together the fields of psycholinguistics and variational sociolinguistics under the following description:
Traditionally, linguistic variation has been the concern of (variationist) sociolinguistics and work in language processing has fallen under the domain of psycholinguistics and cognitive science. Recently, however, this apparent division has been questioned because work in sociolinguistics now encompasses experimental techniques and work in psycholinguistics has begun to engage with variable naturalistic data. As the interests of these fields converge, new questions about the relationship between linguistic variation and social cognition have been generated e.g. How is linguistic variation stored in the mind? How is the ‘linguistic’ and the ‘extra-linguistic’ linked? How do we best model these connections?
We are pleased to announce the continuation of the discussion at VALP6 in Vigo. This conference provides a venue for researchers coming from traditionally distinct fields, such as sociolinguistics, psycholinguistics, cognitive science, experimental phonetics, syntax and pragmatics, who work on the relationship between linguistic variation, in its widest sense, and language processing.
Plenary speakers
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Montserrat Comesaña
(Universidade do Minho)
Montserrat Comesaña is a psycholinguist working at the Psychology Research Center (CIPsi, University of Minho) in Portugal. She obtained her PhD in Basic Psychology from the University of Santiago de Compostela. The primary interest that characterizes her research lies in the organization and processing of lexical representations in first and second/foreign languages, their cognitive and neural underpinnings, and how language organization changes throughout the lifespan. A representative feature of her research is the combination of methods, taking advantage of their respective strengths to address specific research questions on the impact of lexical and sublexical factors in visual word recognition and production and sentence processing. This variety of methods is noticeable across her published work, in which behavioral methods (Comesaña et al., 2021, Frontiers in Psychology), event-related potentials (e.g., Comesaña et al., 2012, NL), and eye-tracking techniques were used (e.g., Soares, Oliveira, Ferreira, Comesaña, Ferré, Fraga, & Macedo, 2018).
show lessThe impact of bilingualism on cognitive development and academic success
Over the last decades, research on bilingualism has attracted the interest of numerous political entities, business leaders, and academic experts. This interest is fuelled not only because more than half the world’s population is bilingual (Grosjean, 2022), but also because increased language competence fosters employability and economic growth (COM, 2008). In fact, the European Union defines multilingualism as a key objective of its language policy and the “Education and Training 2020” strategic framework, leading most member states to strengthen the acquisition of a second language (L2) as part of their educational curricula. In this talk I will be discussing about the impact of the percentage of hours dedicated to second language (L2) learning (often made operative as the number of academic subjects whose vehicular language is the L2) on the first language (L1-Portuguese) skills at the sublexical, lexical and morphosyntactic levels and in psychoeducational factors such as attitude and mental openness. Note that there is no systematic study in the Iberian Peninsula, and more specifically in Portugal, thus far, that has examined this issue. This is of special relevance because empirical data regarding the effect of L2 learning in L1 skills are inconsistent, probably because similarities between languages affect language transfer, and also because of methodological differences across studies (see Pavlenko, 2000). Indeed, although there is evidence sustaining a beneficial effect of L2 immersion programs in L1 skills (e.g., Bournot-Trites & Tellowicz, 2002; Vender et al., 2021), to the best of my knowledge there are no studies which have examined this issue across schools that differ in the number of subjects that are taught in an L2 (schools including CLIL [Content and Language Integrated Learning] practices). In this regard, objectives are set at three levels: Methodological (developing the first large-scale study on sociolinguistic data and lexical decision latencies in L1 and L2 with children who are learning a L2 in the type of schools above mentioned), empirical (establishing experimental benchmark effects on sublexical and lexical processing and examining their interaction with individual variables such as age, language balance [operationalized in terms of the difference in participants’ daily use of L1 and L2], and age of language acquisition), and theoretical (refining qualitative and quantitative approaches to bilingual research, e.g., Cummins, 2000; Peeters & Dijkstra et al., 2023).
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Natalia Levshina
(Radboud University)
Natalia Levshina is Assistant Professor at the Centre for Language Studies at Radboud University (Nijmegen, The Netherlands). She obtained her PhD in Linguistics from the University of Leuven in 2011, with a quantitative study of variation of Dutch causative constructions. She has published the book Communicative Efficiency: Language Structure and Use (2022, Cambridge University Press), in which she shows how language users minimize processing and articulatory effort by choosing different ways of conveying their message.
show lessCommunicative efficiency, language variation and processing
Communicative efficiency has been a prominent theme in linguistics and cognitive science in the recent decades (Hawkins, 2004; Gibson et al., 2019; Levshina & Moran, 2021; Levshina, 2022). There is plenty of evidence showing that language users try to communicate efficiently, saving time and effort while making sure that they transfer the intended message successfully. In this talk I will discuss how language users save processing costs, in particular, memory costs and the processing costs related to surprisal (e.g., Yngve 1960; Gibson 1998; Hale 2001; Levy 2008), and how this explains grammatical variation in different languages.
One of the ways of saving processing costs is minimization of syntactic dependencies (Ferrer-i-Cancho, 2006; Liu, 2008; Gildea & Temperley, 2010; Futrell et al., 2015) and the domains necessary for recognition of constituents (Hawkins, 2004). These tendencies can be explained by the information locality principle (Futrell & Levy 2017), which predicts that language users prefer orders of words and morphemes that contribute to an efficient trade-off between memory and surprisal costs (Hahn et al. 2021). In my talk I will show how these principles account for many instances of word order variation in languages of the world.
In addition, I will discuss arguments for and against the popular idea that language users tend to keep information density uniform in a sentence, avoiding peaks and troughs in information content. This idea has been known under different names, such as the Constancy Rate Principle, the Smooth Signal Redundancy Hypothesis or the Uniform Information Density Hypothesis (Fenk & Fenk, 1980; Genzel & Charniak 2002; Aylett & Turk 2004; Levy & Jaeger, 2007). Although the tendency to keep information content uniform may be true for transmission of acoustic information, I will argue that the evidence is less convincing when we speak about lexical or grammatical variation, and that the choice of linguistic variants is more naturally explained by the overall tendency to reduce forms that convey highly accessible content (Levshina 2022).
After laying the theoretical foundations, I will use the general principles discussed above to interpret a few well-known grammatical alternations (the Dative and Genitive alternations in English, the particle placement alternation, and some others) from the point of view of communicative efficiency. I will also discuss the forces that constrain and compete with the pressure for efficiency, such as learnability (analogy) and the Principle of No Synonymy (Goldberg 1995).
References
Aylett, M., & Turk, A. (2004). The smooth signal redundancy hypothesis: A functional explanation for relationships between redundancy, prosodic prominence, and duration in spontaneous speech. Language and Speech, 47(1), 31–56.
Fenk, A., & Fenk, G. (1980). Konstanz im Kurzzeitgedächtnis – Konstanz im sprachlichen Informationsfluß. Zeitschrift für experimentelle und angewandte Pshychologie XXVII, 3, 400–414.
Ferrer-i-Cancho, R. (2006). Why do syntactic links not cross? Europhysics Letters, 76(6), 1228.
Futrell, R., & Levy, R. (2017). Noisy-context surprisal as a human sentence processing cost model. In M. Lapata, Ph. Blunsom & A. Koller (Eds.), Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers (pp. 688–698). EACL. https://www.aclweb.org/anthology/E17-1065
Futrell, R., Mahowald K., & Gibson, E. (2015). Large-scale evidence of dependency length minimization in 37 languages. Proceedings of the National Academy of Sciences, 112(33), 10336–10341.
Genzel, D., & Charniak, E. (2002). Entropy rate constancy in text. In Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (pp. 199–206). ACL. https://aclanthology.org/P02-1026.
Gibson, E. (1998). Linguistic complexity: locality of syntactic dependencies. Cognition, 68, 1–76.
Gibson, E., Futrell, R., Piantadosi, S., Dautriche, I., Mahowald, K., Bergen, L., & Levy, R. (2019). How efficiency shapes human language. Trends in Cognitive Science, 23(5), 389-407. https://doi.org/10.1016/j.tics.2019.02.003
Gildea, D., & Temperley, D. (2010). Do grammars minimize dependency length? Cognitive Science, 34(2), 286–310.
Goldberg, A. E. (1995). Constructions: A Construction Grammar Approach to Argument Structure. University of Chicago Press.
Hahn, M., Degen, J., & Futrell, R. (2021). Modeling word and morpheme order in natural language as an efficient trade-off of memory and surprisal. Psychological Review, 128(4), 726–756. https://doi.org/10.1037/rev0000269
Hale, J. (2001). A probabilistic Earley parser as a psycholinguistic model. In Proceedings of the Second Meeting of the North American Chapter of the Association for Computational Linguistics (pp. 159–166). https://aclanthology.org/N01-1021.
Hawkins, J. A. (2004). Efficiency and Complexity in Grammars. Oxford University Press.
Levshina, N. (2022). Communicative Efficiency: Language Structure and Use. Cambridge University Press.
Levshina, N., & Moran, S. (2021). Efficiency in human languages: corpus evidence for universal principles. Linguistics Vanguard, 7(s3), 20200081. https://doi.org/10.1515/lingvan-2020-0081.
Levy, R. (2008). Expectation-based syntactic comprehension. Cognition 106: 1126–1177.
Levy, R., & Jaeger, T. F. (2007). Speakers optimize information density through syntactic reduction. In B. Schlökopf, J. Platt & Th. Hoffman (Eds.), Advances in Neural Information Processing Systems (NIPS), vol. 19 (pp. 849–856). MIT Press.
Liu, H. (2008). Dependency distance as a metric of language comprehension difficulty. Journal of Cognitive Science, 9(2), 159–191.
Yngve, V. H. (1960). A model and an hypothesis for language structure. Proceedings of the American Philosophical Society, 104(5), 444–466.
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Prof. Dr. Hans-Jörg Schmid
(Ludwig-Maximilians-Universität München)
Hans-Jörg Schmid is Full Professor and Chair of Modern English Linguistics at LMU Munich, Germany. His research has been devoted to a wide range of fields in linguistics including linguistic theory, cognitive linguistics, lexical semantics, syntax, word-formation, pragmatics, sociolinguistics and language change. In his recent book, entitled The Dynamics of the Linguistic System. Usage, Conventionalization and Entrenchment (2020, OUP), he developsa unified model of how language works, integrating cognitive, social and pragmatic aspects, to explain linguistic structure, variation and change.
show lessCan our understanding of entrenchment explain or even predict the structure and communicative effects of linguistic variation?
According to the usage-based commitment (see, e.g. Langacker 1987, Bybee 2010), grammar and linguistic knowledge emerge from usage. As has been shown in sociolinguistics, “grammar” (here taken to include phonology and the lexicon) is inherently variable on the levels of forms, meanings and functions, depending on contextual, situational and social factors. Therefore, if we take the usage-based commitment seriously, linguistic variation should also emerge from usage via the same processes that transform usage into grammar. Relying on the predictions of the Entrenchment-and-Conventionalization Model (Schmid 2020), I discuss in which way the key cognitive process of entrenchment contributes to shaping the structure and communicative effects of linguistic variation. This discussion brings together hypotheses about the process of entrenchment, on the one hand, and corresponding findings on the structure of linguistic, situational and social variation, on the other.
To test the idea whether entrenchment can explain or even predict the structure of variation I discuss results and insights from a number of recent sociolinguistic studies, including Schmid et al. (2021). In addition, I will discuss the methodological implications of a cognitive usage-based approach for sociolinguistic investigations.
References
Bybee, J. L. (2010). Language, usage and cognition. Cambridge University Press.
Langacker, R. W. (1988). A usage-based model. In B. Rudzka-Ostyn (Ed.), Topics in cognitive linguistics, Benjamins, 127-163.
Schmid, H.-J. (2020). The dynamics of the linguistic system. Usage, conventionalization, and entrenchment. Oxford University Press.
Schmid, H.-J., Würschinger, Q., Fischer, S., & Küchenhoff, H. (2021). That’s cool. Computational sociolinguistic methods for investigating individual lexico-grammatical variation. Frontiers in Artificial Intelligence, 3. https://doi.org/10.3389/frai.2020.547531
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