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Psycholinguistic Research on Inflectional Morphology in the Romance Languages  

Claudia Marzi and Vito Pirrelli

Over the past decades, psycholinguistic aspects of word processing have made a considerable impact on views of language theory and language architecture. In the quest for the principles governing the ways human speakers perceive, store, access, and produce words, inflection issues have provided a challenging realm of scientific inquiry, and a battlefield for radically opposing views. It is somewhat ironic that some of the most influential cognitive models of inflection have long been based on evidence from an inflectionally impoverished language like English, where the notions of inflectional regularity, (de)composability, predictability, phonological complexity, and default productivity appear to be mutually implied. An analysis of more “complex” inflection systems such as those of Romance languages shows that this mutual implication is not a universal property of inflection, but a contingency of poorly contrastive, nearly isolating inflection systems. Far from presenting minor faults in a solid, theoretical edifice, Romance evidence appears to call into question the subdivision of labor between rules and exceptions, the on-line processing vs. long-term memory dichotomy, and the distinction between morphological processes and lexical representations. A dynamic, learning-based view of inflection is more compatible with this data, whereby morphological structure is an emergent property of the ways inflected forms are processed and stored, grounded in universal principles of lexical self-organization and their neuro-functional correlates.


Psycholinguistic Methods and Tasks in Morphology  

Daniel Schmidtke and Victor Kuperman

Lexical representations in an individual mind are not given to direct scrutiny. Thus, in their theorizing of mental representations, researchers must rely on observable and measurable outcomes of language processing, that is, perception, production, storage, access, and retrieval of lexical information. Morphological research pursues these questions utilizing the full arsenal of analytical tools and experimental techniques that are at the disposal of psycholinguistics. This article outlines the most popular approaches, and aims to provide, for each technique, a brief overview of its procedure in experimental practice. Additionally, the article describes the link between the processing effect(s) that the tool can elicit and the representational phenomena that it may shed light on. The article discusses methods of morphological research in the two major human linguistic faculties—production and comprehension—and provides a separate treatment of spoken, written and sign language.


Quantitative Methods in Morphology: Corpora and Other “Big Data” Approaches  

Marco Marelli

Corpora are an all-important resource in linguistics, as they constitute the primary source for large-scale examples of language usage. This has been even more evident in recent years, with the increasing availability of texts in digital format leading more and more corpus linguistics toward a “big data” approach. As a consequence, the quantitative methods adopted in the field are becoming more sophisticated and various. When it comes to morphology, corpora represent a primary source of evidence to describe morpheme usage, and in particular how often a particular morphological pattern is attested in a given language. There is hence a tight relation between corpus linguistics and the study of morphology and the lexicon. This relation, however, can be considered bi-directional. On the one hand, corpora are used as a source of evidence to develop metrics and train computational models of morphology: by means of corpus data it is possible to quantitatively characterize morphological notions such as productivity, and corpus data are fed to computational models to capture morphological phenomena at different levels of description. On the other hand, morphology has also been applied as an organization principle to corpora. Annotations of linguistic data often adopt morphological notions as guidelines. The resulting information, either obtained from human annotators or relying on automatic systems, makes corpora easier to analyze and more convenient to use in a number of applications.