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1
Characterizing News Portrayal of Civil Unrest in Hong Kong, 1998–2020 ...
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2
Jibes & Delights: A Dataset of Targeted Insults and Compliments to Tackle Online Abuse​ ...
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3
Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
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4
Formalization of AMR Inference via Hybrid Logic Tableaux ...
Goldner, Eli Tecumseh. - : Brandeis University, 2022
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5
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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6
Dependency Patterns of Complex Sentences and Semantic Disambiguation for Abstract Meaning Representation Parsing ...
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7
Phrase-Level Action Reinforcement Learning for Neural Dialog Response Generation ...
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8
10D: Phonology, Morphology and Word Segmentation #1 ...
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9
Sample-efficient Linguistic Generalizations through Program Synthesis: Experiments with Phonology Problems ...
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10
19th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology - Part 2 ...
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11
18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology - Part 1 ...
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12
SpeakEasy Pronunciation Trainer: Personalized Multimodal Pronunciation Training ...
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13
The Match-Extend Serialization Algorithm in Multiprecedence ...
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14
Recognizing Reduplicated Forms: Finite-State Buffered Machines ...
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15
Correcting Chinese Spelling Errors with Phonetic Pre-training ...
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16
PLOME: Pre-training with Misspelled Knowledge for Chinese Spelling Correction ...
Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.233 Abstract: Chinese spelling correction (CSC) is a task to detect and correct spelling errors in texts. CSC is essentially a linguistic problem, thus the ability of language understanding is crucial to this task. In this paper, we propose a Pre-trained masked Language model with Misspelled knowledgE (PLOME) for CSC, which jointly learns how to understand language and correct spelling errors. To this end, PLOME masks the chosen tokens with similar characters according to a confusion set rather than the fixed token ``[MASK]" as in BERT. Besides character prediction, PLOME also introduces pronunciation prediction to learn the misspelled knowledge on phonic level. Moreover, phonological and visual similarity knowledge is important to this task. PLOME utilizes GRU networks to model such knowledge based on characters' phonics and strokes. Experiments are conducted on widely used benchmarks. Our method achieves superior performance against state-of-the-art ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://underline.io/lecture/25563-plome-pre-training-with-misspelled-knowledge-for-chinese-spelling-correction
https://dx.doi.org/10.48448/hvyh-zh15
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17
SpeakEasy Pronunciation Trainer: Personalized Multimodal Pronunciation Training ...
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18
Including Signed Languages in Natural Language Processing ...
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19
Quantification: the view from natural language generation ...
Carstensen, Kai-Uwe. - : Universitätsbibliothek Siegen, 2021
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20
When is Char Better Than Subword: A Systematic Study of Segmentation Algorithms for Neural Machine Translation ...
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