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The role of object novelty and pragmatic reasoning in referent selection and word learning (Study 2b) ...
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Disambiguation of Medical Abbreviations in French with Supervised Methods
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In: Studies in Health Technology and Informatics ; https://hal.archives-ouvertes.fr/hal-03335532 ; Studies in Health Technology and Informatics, 2021, ⟨10.3233/shti210171⟩ (2021)
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The role of object novelty and nameability in disambiguation and word learning ...
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Perceptual vowel contrast reduction in Australian English /l/-final rimes
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In: Laboratory Phonology: Journal of the Association for Laboratory Phonology; Vol 12, No 1 (2021); 9 ; 1868-6354 (2021)
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Italian Sense Inventory
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Poli, Francesca. - : Università di Pisa, 2021. : Istituto di Linguistica Computazionale “A. Zampolli” - Consiglio Nazionale delle Ricerche (ILC-CNR), 2021
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Not this, but that.' Exploring disambiguation in the context of multilingual word learning ...
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Word Sense Disambiguation Using Prior Probability Estimation Based on the Korean WordNet
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In: Electronics; Volume 10; Issue 23; Pages: 2938 (2021)
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A Knowledge-Based Sense Disambiguation Method to Semantically Enhanced NL Question for Restricted Domain
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In: Information ; Volume 12 ; Issue 11 (2021)
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The Integration of Linguistic and Geospatial Features Using Global Context Embedding for Automated Text Geocoding
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In: ISPRS International Journal of Geo-Information ; Volume 10 ; Issue 9 (2021)
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Improving the Performance of Vietnamese&ndash ; Korean Neural Machine Translation with Contextual Embedding
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In: Applied Sciences ; Volume 11 ; Issue 23 (2021)
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Abstract:
With the recent evolution of deep learning, machine translation (MT) models and systems are being steadily improved. However, research on MT in low-resource languages such as Vietnamese and Korean is still very limited. In recent years, a state-of-the-art context-based embedding model introduced by Google, bidirectional encoder representations for transformers (BERT), has begun to appear in the neural MT (NMT) models in different ways to enhance the accuracy of MT systems. The BERT model for Vietnamese has been developed and significantly improved in natural language processing (NLP) tasks, such as part-of-speech (POS), named-entity recognition, dependency parsing, and natural language inference. Our research experimented with applying the Vietnamese BERT model to provide POS tagging and morphological analysis (MA) for Vietnamese sentences,, and applying word-sense disambiguation (WSD) for Korean sentences in our Vietnamese&ndash ; Korean bilingual corpus. In the Vietnamese&ndash ; Korean NMT system, with contextual embedding, the BERT model for Vietnamese is concurrently connected to both encoder layers and decoder layers in the NMT model. Experimental results assessed through BLEU, METEOR, and TER metrics show that contextual embedding significantly improves the quality of Vietnamese&ndash ; Korean NMT.
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Keyword:
bidirectional encoder representations from transformers; Korean–Vietnamese machine translation; neural machine translation; part-of-speech; word-sense disambiguation
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URL: https://doi.org/10.3390/app112311119
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NERWS: Towards Improving Information Retrieval of Digital Library Management System Using Named Entity Recognition and Word Sense
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In: Big Data and Cognitive Computing ; Volume 5 ; Issue 4 (2021)
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SemEval-2021 Task 2: Multilingual and Cross-lingual Word-in-Context Disambiguation (MCL-WiC) ...
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SemEval-2021 Task 2: Multilingual and Cross-lingual Word-in-Context Disambiguation (MCL-WiC) ...
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TERMS AND TEXTS: THE FUNCTIONALITY OF EDITORIAL-POLYGRAPHIC TERMS ...
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TERMS AND TEXTS: THE FUNCTIONALITY OF EDITORIAL-POLYGRAPHIC TERMS ...
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Not this, but that.' Exploring disambiguation in the context of multilingual word learning
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Semantically-oriented text planning for automatic summarization
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In: TDX (Tesis Doctorals en Xarxa) (2021)
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