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.
Daniel Schmidtke and Victor Kuperman
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.