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Diachronic treebanks allow for a new approach to diachronic studies of syntactic phenomena. These papers report research on various diachronic matters supported such by evidence, covering a wide range of languages, including English, French, Russian, Latin and Ancient Greek. Originally published as Diachronica 35:3 (2018).

The book will appeal to scholars and advanced students of morphology, syntax, computational linguistics and natural language processing (NLP). It provides a critical and practical guide to computational techniques for handling morphological and syntactic phenomena, showing how these techniques have been used and modified in practice. The authors discuss the nature and uses of syntactic parsers and examine the problems and opportunities of parsing algorithms for finite-state, context-free and various context-sensitive grammars. They relate approaches for describing syntax and morphology to formal mechanisms and algorithms, and present well-motivated approaches for augmenting grammars with weights or probabilities.

This book is a textbook on R, a programming language and environment for statistical analysis and visualization. Its primary aim is to introduce R as a research instrument in quantitative Interactional Linguistics. Focusing on visualization in R, the book presents original case studies on conversational talk-in-interaction based on corpus data and explains in good detail how key graphs in the case studies were programmed in R. It also includes task sections to enable readers to conduct their own research and compute their own visualizations in R. Both the code underlying the key graphs in the case studies and the datasets used in the case studies as well as in the task sections are made available on the book's companion website.

Interest in statistical natural language generation is rapidly increasing. This work sheds important light from theoretical linguistics on the type of information crucial to statistical NLG algorithms.

The series Quantitative Linguistics publishes books on all aspects of quantitative methods and models in linguistics, text analysis and related research fields. Specifically, the scope of the series covers the whole spectrum of theoretical and empirical research, ultimately striving for an exact mathematical formulation and empirical testing of hypotheses: observation and description of linguistic data, application of methods and models, discussion of methodological and epistemological issues, modelling of language and text phenomena.

Recent research in grounded language learning has seen remarkable success due to advances in large vision and language models (VLMs). However, these models (i) are extremely costly to train and update; (ii) struggle with generalisation; and (iii) do not support continual learning. In this paper, we introduce baby-ds integrating the Dynamic Syntax (DS) framework with automated planning within the multimodal BabyAI platform as a testbed. We provide methods whereby DS lexicons are induced continually from teacher demonstrations within BabyAI. We study (i–iii) by experimenting with the compositional complexity of natural language instructions in the data to compare data efficiency, generalisation, and continual learning properties of baby-ds with a simple neural model. The results show that the baby-ds model: (i) needs much less data than the neural model to reach threshold performance; (ii) generalises much faster to more complex instructions; and (iii) is a more effective continual learner. We argue that it is the attendant linguistic bias within DS and the rich inferential power of TTR that enables (i–iii), highlighting the importance of further research on hybrid grammar–neural approaches. Finally, we discuss several important limitations of baby-ds and sketch a path forward for further DS research.

It is a well-known fact that across the world's languages there is a fairly strong asymmetry in the affixation of grammatical material, in that suffixes considerably outnumber prefixes in typological databases. This article argues that prosody, specifically prosodie phrasing, plays an important part in bringing about this asymmetry. Prosodie word and phrase boundaries may occur after a clitic function word preceding its lexical host with sufficient frequency so as to impede the fusion required for affixhood. Conversely, prosodie boundaries rarely, if ever, occur between a lexical host and a clitic function word following it. Hence, prosody does not impede the fusion process between lexical hosts and postposed function words, which therefore become affixes more easily. Evidence for the asymmetry in prosodie phrasing is provided from two sources: disfluencies, and ditropic cliticization, that is, the fact that grammatical PROclitics may be phonological ENclitics (i.e. phrased with a preceding host), but grammatical enclitics are never phonological proclitics. Earlier explanations for the suffixing preference have neglected prosody almost completely and thus also missed the related asymmetry in ditropic cliticization. More importantly, the evidence from prosodie phrasing suggests a new venue for explaining the suffixing preference. The asymmetry in prosodie phrasing, which, according to the hypothesis proposed here, is a major factor underlying the suffixing preference, has a natural basis in the mechanics of turn-taking as well as in the mechanics of speech production.

Purpose: The goal of this study was to examine online and off-line sentence processing using Korean language relative clause sentences between children with specific language impairment (SLI) and children with typical development (TD). Method: Twenty-four children with TD and 19 children with SLI participated in this study. Children completed online and off-line sentence-processing tasks using relative clause sentences. The response time (RT) data obtained from the online processing task were analyzed at each word position and between adjacent words for items answered both correctly and incorrectly on the off-line comprehension task. A linear mixed-effects model and a generalized linear mixed effects model were used to analyze the performances on the online/off-line sentence-processing task between the two groups. Results: The results revealed that the processing pattern of RTs on the online processing task differed between the two groups, such that the SLI group did not show the predicted RT increase while the TD group did. Also, the SLI group processed each word with comparable or faster reading rates than the TD group. On the off-line comprehension task, the SLI group performed poorly compared to the TD group. Conclusions: Processing of syntactically complex sentences differed between the TD and SLI groups, such that the SLI group had lower accuracy on the off-line comprehension task and was less efficient on the online processing task as compared to the TD group. These results mainly support the syntactic deficit account in children with SLI.