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Under-Represented Speech Dataset from Open Data: Case Study on the Romanian Language
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Multilingual Multiword Expression Identification Using Lateral Inhibition and Domain Adaptation
Abstract : Correctly identifying multiword expressions (MWEs) is an important task for most natural language processing systems since their misidentification can result in ambiguity and misunderstanding of the underlying text. In this work, we evaluate the performance of the mBERT model for MWE identification in a multilingual context by training it on all 14 languages available in version 1.2 of the PARSEME corpus.
[2304.11350] Romanian Multiword Expression Detection Using Multilingual Adversarial Training and Lateral Inhibition
arXiv:2304.11350 (cs) Download a PDF of the paper titled Romanian Multiword Expression Detection Using Multilingual Adversarial Training and Lateral Inhibition, by Andrei-Marius Avram and 1 other authors Download PDF Submission history From: Andrei-Marius Avram [ view email] [v1] Sat, 22 Apr 2023 09:10:49 UTC (7,110 KB) Bibliographic Tools Bibliographic Explorer Toggle Bibliographic Explorer () Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart...
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