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Sequence Models for Computational Etymology of Borrowings ...
Abstract: Read paper: https://www.aclanthology.org/2021.findings-acl.353 Abstract: We computationally model the processes of word borrowing from a donor word to an incorporated word, and vice versa, by answering two questions: (1) what does a word look like if it is incorporated into another language, and in the opposite direction (2) where did a word come from? We employ neural sequence models, focusing on six specific borrowing relations: calques, partial calques, semantic loans, phono-semantic matches, transliterations, and generic borrowings. We experiment with several model variants, including LSTM encoder-decoders, copy attention, and Transformers, along with several data distribution and preprocessing scenarios. We find that the quality of data strongly influences the performance of models, with low character edit distance between model predictions and the gold words. ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Neural Network; Semantics
URL: https://underline.io/lecture/26444-sequence-models-for-computational-etymology-of-borrowings
https://dx.doi.org/10.48448/xv8m-yf67
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Modeling Color Terminology Across Thousands of Languages ...
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