Dear colleagues,
Happy new year ! We are extending the deadline for this call to the 15th of February. At the request of some authors, we also adapted the most recent JLM LaTeX template so that it be compatible with overleaf, it can be found here: https://fr.overleaf.com/latex/templates/template-for-journal-of-language-mod...
Please find below the updated call:
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We invite researchers in the broad area of computational morphology to submit their recent, unpublished work to a special issue of the Journal of Language Modelling https://jlm.ipipan.waw.pl/index.php/JLMhttps://jlm.ipipan.waw.pl/index.php/JLM.
Motivation:
Computational techniques have a long history of use in the study of morphology, where they have been used both for practical tasks such as the analysis and production of complex word forms and for theoretical ones such as structural and informational analysis of morphological systems. As both systems and datasets improve, these techniques are increasingly developed and evaluated on a typologically diverse array of languages, including many which are endangered or lack large-scale resources. Detailed comparisons across languages can help to reveal typological biases or assumptions within existing computational techniques [1, 2]. Alternatively, computational methods and analyses can also shed light on questions within linguistic typology [3, 4, 5, 6].
The goal of this special issue is to bring researchers from multiple communities together in exploring issues of linguistic typology across a wide range of different languages and phenomena. We encourage the submission of work on endangered or less-studied languages. The Journal of Language Modelling is a free (for readers and authors alike) open-access peer-reviewed journal. All articles are peer-reviewed by at least 3 reviewers, usually including at least one member of the Editorial Board.
Topics of interest:
- Typological clustering or classification of languages - Investigation of particular linguistic features which improve or detract from the performance of computational morphology tools - Comparison of morphological structures (e.g., inflection classes, implicative networks) across typologically different languages - Investigation of diachronic typological change using computational methods - Creation, curation or analysis of typological databases via computational methods
Submissions:
The submissions should be journal papers, not proceedings papers, totalling 25-50 pages, excluding references.
Authors are advised to use the online manuscript submission for the journal. Make sure to select the special issue when asked to provide the article type. More information, including formatting instructions for authors can be found on the journal's webpage at: https://jlm.ipipan.waw.pl/index.php/JLM/about/submissions. An adaptation of the LaTeX template for overleaf can be found at: https://fr.overleaf.com/latex/templates/template-for-journal-of-language-mod....
Important dates:
Call for papers issued: 15/7/2022 Submissions due: 15/1/2023 --- extended to 15/02/2023 Author notification: Spring 2023
Guest editors:
Sacha Beniamine (University of Surrey) Micha Elsner (The Ohio State University) Katharina Kann (University of Colorado, Boulder)
References
[1] Ryan Cotterell, Christo Kirov, John Sylak-Glassman, David Yarowsky, Jason Eisner, and Mans Hulden. 2016a. The SIGMORPHON 2016 shared Task— Morphological reinflection. In Proceedings of the 14th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology, pages 10–22, Berlin, Germany. Association for Computational Linguistics.
[2] Huiming Jin, Liwei Cai, Yihui Peng, Chen Xia, Arya McCarthy, and Katharina Kann. 2020. Unsupervised morphological paradigm completion. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 6696– 6707, Online. Association for Computational Linguistics.
[3] Neil Rathi, Michael Hahn, and Richard Futrell. 2021. An Information-Theoretic Characterization of Morphological Fusion. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 10115–10120, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
[4] Parker, J., Reynolds, R., & Sims, A. (2022). Network Structure and Inflection Class Predictability: Modeling the Emergence of Marginal Detraction. In A. Sims, A. Ussishkin, J. Parker, & S. Wray (Eds.), Morphological Diversity and Linguistic Cognition (pp. 247-281). Cambridge: Cambridge University Press. DOI: 10.1017/9781108807951.010
[5] Guzmán Naranjo, Matías and Becker, Laura. Statistical bias control in typology. Linguistic Typology, to appear, 2021. DOI: 10.1515/lingty-2021-0002
[6] Sacha Beniamine. 2021. One lexeme, many classes: Inflection class systems as lattices. In Berthold Crysmann & Manfred Sailer (eds.), One-to-many relations in morphology, syntax, and semantics, 23--51. Berlin: Language Science Press. DOI: 10.5281/zenodo.4729789