Thinking About Multiword Constructions: Usage‐Based Approaches to Acquisition and Processing

Usage‐based approaches to language hold that we learn multiword expressions as patterns of language from language usage, and that knowledge of these patterns underlies fluent language processing. This paper explores these claims by focusing upon verb–argument constructions (VACs) such as “V(erb) about n(oun phrase).” These are productive constructions that bind syntax, lexis, and semantics. It presents (a) analyses of usage patterns of English VACs in terms of their grammatical form, semantics, lexical constituency, and distribution patterns in large corpora; (b) patterns of VAC usage in child‐directed speech and child language acquisition; and (c) investigations of VAC free‐association and psycholinguistic studies of online processing. We conclude that VACs are highly patterned in usage, that this patterning drives language acquisition, and that language processing is sensitive to the forms of the syntagmatic construction and their distributional statistics, the contingency of their association with meaning, and spreading activation and prototypicality effects in semantic reference. Language users have rich implicit knowledge of the statistics of multiword sequences.Ellis & Ogden examine the acquisition, processing and usage of verb‐argument constructions in English. They analyze the semantic, grammatical and distributional features of these multiword constructions in a large corpus; describes their use by both L1 and L2 learners; and reviews psycholinguistic findings on their processing by native and non‐native speakers. The findings demonstrate that language users have rich implicit statistical knowledge of multiword patterns and use this knowledge in learning and processing.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137734/1/tops12256.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137734/2/tops12256_am.pd

Cross-lingual transfer learning and multitask learning for capturing multiword expressions

This is an accepted manuscript of an article published by Association for Computational Linguistics in Proceedings of the Joint Workshop on Multiword Expressions and WordNet (MWE-WN 2019), available online: https://www.aclweb.org/anthology/W19-5119 The accepted version of the publication may differ from the final published version.Recent developments in deep learning have prompted a surge of interest in the application of multitask and transfer learning to NLP problems. In this study, we explore for the first time, the application of transfer learning (TRL) and multitask learning (MTL) to the identification of Multiword Expressions (MWEs). For MTL, we exploit the shared syntactic information between MWE and dependency parsing models to jointly train a single model on both tasks. We specifically predict two types of labels: MWE and dependency parse. Our neural MTL architecture utilises the supervision of dependency parsing in lower layers and predicts MWE tags in upper layers. In the TRL scenario, we overcome the scarcity of data by learning a model on a larger MWE dataset and transferring the knowledge to a resource-poor setting in another language. In both scenarios, the resulting models achieved higher performance compared to standard neural approaches

Linking adult second language learning and diachronic change:a cautionary note

It has been suggested that the morphological complexity of a language is negatively correlated with the size of its population of speakers. This relationship may be driven by the proportion of non-native speakers, among other things, and reflects adaptations to learning constraints imposed by adult language learners. Here we sound a note of caution with respect to these claims by arguing that (a) morphological complexity is defined in somewhat contradictory ways and hence not straightforward to measure, and (b) there is insufficient evidence to suggest that children’s cognitive limitations support mechanisms beneficial for learning of complex morphology relative to adults. We suggest that considering the informational value of morphological cues may be a better way to capture learnability of morphology. To settle the issue of how age related constraints on learning might impact language change, more cross-linguistic studies comparing learning trajectories of different second languages and laboratory experiments examining language transmission in children and adults are needed

Expression of Affect and the Emergence of Language

The relation between infant affect expression and the emergence of language was studied in 6 girls and 6 boys, from 9 months to 2 years of age. First words (FW) and vocabulary spurt (VS) were identified in the infants' transition from prespeech vocalizing to the emergence of language. Their expressions of affect were coded for the gradient properties of valence (positive, negative, neutral, mixed, equivocal) and intensity. Frequency of nonneutral affect expression at FW and VS was positively correlated with age at FW and VS (p < .02), meaning that the more frequently the children expressed emotion, the older the age of language achievements. Time spent in neutral affect at FW and VS was negatively correlated with age at FW and VS (p < .02); the more time spent in neutral affect, the younger the age of language achievements. In addition, the measures of affect at VS predicted the eventual transition to multiword speech, with more time spent in neutral affect expression at VS negatively correlated with earlier age in the use of sentences. We propose that neutral affect supports the early transition to language by allowing the reflective stance required for language learning, and has its antecedents in the quiet alert states which support the cognitive activity of early infancy

Using distributional similarity to organise biomedical terminology

We investigate an application of distributional similarity techniques to the problem of structural organisation of biomedical terminology. Our application domain is the relatively small GENIA corpus. Using terms that have been accurately marked-up by hand within the corpus, we consider the problem of automatically determining semantic proximity. Terminological units are dened for our purposes as normalised classes of individual terms. Syntactic analysis of the corpus data is carried out using the Pro3Gres parser and provides the data required to calculate distributional similarity using a variety of dierent measures. Evaluation is performed against a hand-crafted gold standard for this domain in the form of the GENIA ontology. We show that distributional similarity can be used to predict semantic type with a good degree of accuracy

On becoming a physicist of mind

In 1976, the German Max Planck Society established a new research enterprise in psycholinguistics, which became the Max Planck Institute for Psycholinguistics in Nijmegen, the Netherlands. I was fortunate enough to be invited to direct this institute. It enabled me, with my background in visual and auditory psychophysics and the theory of formal grammars and automata, to develop a long-term chronometric endeavor to dissect the process of speaking. It led, among other work, to my book Speaking (1989) and to my research team's article in Brain and Behavioral Sciences “A Theory of Lexical Access in Speech Production” (1999). When I later became president of the Royal Netherlands Academy of Arts and Sciences, I helped initiate the Women for Science research project of the Inter Academy Council, a project chaired by my physicist sister at the National Institute of Standards and Technology. As an emeritus I published a comprehensive History of Psycholinguistics (2013). As will become clear, many people inspired and joined me in these undertakings