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Chinese character decomposition for neural MT with multi-word expressions
In: Han, Lifeng orcid:0000-0002-3221-2185 , Jones, Gareth J.F. orcid:0000-0003-2923-8365 , Smeaton, Alan F. orcid:0000-0003-1028-8389 and Bolzoni, Paolo (2021) Chinese character decomposition for neural MT with multi-word expressions. In: 23rd Nordic Conference on Computational Linguistics (NoDaLiDa 2021), 31 May- 2 June 2021, Reykjavik, Iceland (Online). (In Press) (2021)
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2
Dependency Patterns of Complex Sentences and Semantic Disambiguation for Abstract Meaning Representation Parsing ...
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3
Phrase-Level Action Reinforcement Learning for Neural Dialog Response Generation ...
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4
10D: Phonology, Morphology and Word Segmentation #1 ...
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5
Sample-efficient Linguistic Generalizations through Program Synthesis: Experiments with Phonology Problems ...
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6
19th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology - Part 2 ...
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7
18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology - Part 1 ...
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8
SpeakEasy Pronunciation Trainer: Personalized Multimodal Pronunciation Training ...
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9
The Match-Extend Serialization Algorithm in Multiprecedence ...
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10
Recognizing Reduplicated Forms: Finite-State Buffered Machines ...
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11
Correcting Chinese Spelling Errors with Phonetic Pre-training ...
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12
PLOME: Pre-training with Misspelled Knowledge for Chinese Spelling Correction ...
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13
SpeakEasy Pronunciation Trainer: Personalized Multimodal Pronunciation Training ...
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14
Including Signed Languages in Natural Language Processing ...
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15
Quantification: the view from natural language generation ...
Carstensen, Kai-Uwe. - : Universitätsbibliothek Siegen, 2021
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16
When is Char Better Than Subword: A Systematic Study of Segmentation Algorithms for Neural Machine Translation ...
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The Reading Machine: a Versatile Framework for Studying Incremental Parsing Strategies ...
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18
To POS Tag or Not to POS Tag: The Impact of POS Tags on Morphological Learning in Low-Resource Settings ...
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19
Superbizarre Is Not Superb: Derivational Morphology Improves BERT's Interpretation of Complex Words ...
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20
HIT - A Hierarchically Fused Deep Attention Network for Robust Code-mixed Language Representation ...
Abstract: Read paper: https://www.aclanthology.org/2021.findings-acl.407 Abstract: Understanding linguistics and morphology of resource-scarce code-mixed texts remains a key challenge in text processing. Although word embedding comes in handy to support downstream tasks for low-resource languages, there are plenty of scopes in improving the quality of language representation particularly for code-mixed languages. In this paper, we propose HIT, a robust representation learning method for code-mixed texts. HIT is a hierarchical transformer-based framework that captures the semantic relationship among words and hierarchically learns the sentence-level semantics using a fused attention mechanism. HIT incorporates two attention modules, a multi-headed self-attention and an outer product attention module, and computes their weighted sum to obtain the attention weights. Our evaluation of HIT on one European (Spanish) and five Indic (Hindi, Bengali, Tamil, Telugu, and Malayalam) languages across four NLP tasks on eleven ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Neural Network; Semantics
URL: https://underline.io/lecture/26498-hit---a-hierarchically-fused-deep-attention-network-for-robust-code-mixed-language-representation
https://dx.doi.org/10.48448/p5mt-zn80
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