The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist. RZ, has received funding from Pontificia Universidad Católica del Perú (PUCP) through the project (604 DGI-PUCP) ¿Gramáticas que mueren?: Aproximación crítica a la obsolescencia de las lenguas desde la documentación y la tipología lingüísticas, las ciencias de la información y la inteligencia artificial. ERC Grant #715618, "Computer-Assisted Language Comparison"). TT, JML, have received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: All data and code files are available from as PyBor: A Python library for borrowing detection.įunding: JEM, has received funding and encouragement from the Graduate School of the Pontificia Universidad Católica del Perú (PUCP) through the Huiracocha-2019 scholarship program ( ). Received: AugAccepted: NovemPublished: December 9, 2020Ĭopyright: © 2020 Miller et al. Based on our detailed findings, however, we express hope that they could prove to be useful in integrated approaches that take multi-lingual information into account.Ĭitation: Miller JE, Tresoldi T, Zariquiey R, Beltrán Castañón CA, Morozova N, List J-M (2020) Using lexical language models to detect borrowings in monolingual wordlists. Our results show that phonological and phonotactic clues derived from monolingual language data alone are often not sufficient to detect borrowings when using them in isolation. While the general results appear largely unsatisfying at a first glance, further tests show that the performance of our models improves with increasing amounts of attested borrowings and in those cases where most borrowings were introduced by one donor language alone. Based on a substantially revised dataset in which lexical borrowings have been thoroughly annotated for 41 different languages from different families, featuring a large typological diversity, we use these models to conduct a series of experiments to investigate their performance in mono-lingual borrowing detection. By modeling phonology and phonotactics with the support of Support Vector Machines, Markov models, and recurrent neural networks, we propose a framework for the supervised detection of borrowings in mono-lingual wordlists. In this study, we test how these clues can be exploited in automated frameworks for borrowing detection. One example for this kind of evidence are phonological and phonotactic clues that are especially useful for the detection of recent borrowings that have not yet been adapted to the structure of their recipient languages. Despite the increasing popularity of computational approaches in comparative linguistics, automated approaches to lexical borrowing detection are still in their infancy, disregarding many aspects of the evidence that is routinely considered by human experts. In order to detect borrowings, linguists make use of various strategies, combining evidence from various sources. representation of visual-spatial language and creating access structures for the dictionary.Lexical borrowing, the transfer of words from one language to another, is one of the most frequent processes in language evolution. few resources, no written tradition, and having to create one dictionary for all potential user groups, while others are specific to sign languages, e. Some parallel the challenges minority language lexicographers of spoken languages encounter, e. In this paper, we aim to show and discuss which challenges we encounter while compiling the Digitales Wörterbuch der Deutschen Gebärdensprache (DWDGS), the first corpus-based dictionary of German Sign Language (DGS). When the language in question is also a sign language, circumstances specific to the visual-spatial modality have to be taken into consideration as well. Lexicographers working with minority languages face many challenges. A bilingualized monolingual dictionary of German Sign Language ![]() Anke Müller, Gabriele Langer, Felicitas Otte, Sabrina WählĬreating a dictionary of a signed minority language.
0 Comments
Leave a Reply. |