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Typology based on codable traits has its heyday early in the development of any biological science. In mature disciplines it has long since given way to diachronic models of how complex structures evolve in shifting environments. Linguistic typology is no different. It also faces existential crises from recognition that its categories are dubiously universal and that global samples conceal macroareal biases. To avoid irrelevance, typology should blend into the linguistic landscape. It should defragment by refocusing on interdomain interactions (e.g., between mood and anaphora), and rediscover extreme languages and Sapirean types. Simultaneously, it must decentralize operationally into more manageable and illuminating family-level synchronic-diachronic microtypology.

It is unlikely that local or highly specific typological characteristics of language correlate with other aspects of human culture and history. However, at regional scale, the broad typology of languages does reflect bottlenecks. The paper argues that these regions of high typological similarity are due neither to chance nor long-term convergence, but reflect the initial conditions of settlement. This suggests that regions can be characterised by negative typology, i.e., the absence of globally common traits. Conversely, typological uniformity occurs in mainland Southeast Asia, a region notable for the similarities between language structures. An expansion of the remit of typology can uncover large regional patterns which can be tied to the archaeological narrative of the early expansion of modern humans.

This article first outlines different ways of how psycholinguists have dealt with linguistic diversity and illustrates these approaches with three familiar cases from research on language processing, language acquisition, and language disorders. The second part focuses on the role of morphology and morphological variability across languages for psycholinguistic research. The specific phenomena to be examined are to do with stem-formation morphology and inflectional classes; they illustrate how experimental research that is informed by linguistic typology can lead to new insights.

This paper explores the ways in which the field of natural language processing (NLP) can and does benefit from work in linguistic typology. I describe the recent increase in interest in multilingual natural language processing and give a high-level overview of the field. I then turn to a discussion of how linguistic knowledge in general is incorporated in NLP technology before describing how typological results in particular are used. I consider both rule-based and machine learning approaches to NLP and review literature on predicting typological features as well as that which leverages such features.