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Hierarchical Character Embeddings: Learning Phonological and Semantic
  Representations in Languages of Logographic Origin using Recursive Neural
  Networks

Hierarchical Character Embeddings: Learning Phonological and Semantic Representations in Languages of Logographic Origin using Recursive Neural Networks

20 December 2019
Minh Nguyen
G. Ngo
Nancy F. Chen
ArXivPDFHTML

Papers citing "Hierarchical Character Embeddings: Learning Phonological and Semantic Representations in Languages of Logographic Origin using Recursive Neural Networks"

4 / 4 papers shown
Title
Generic Multi-modal Representation Learning for Network Traffic Analysis
Generic Multi-modal Representation Learning for Network Traffic Analysis
L. Gioacchini
Idilio Drago
Marco Mellia
Zied Ben-Houidi
Dario Rossi
AI4TS
30
1
0
04 May 2024
Breaking the Representation Bottleneck of Chinese Characters: Neural
  Machine Translation with Stroke Sequence Modeling
Breaking the Representation Bottleneck of Chinese Characters: Neural Machine Translation with Stroke Sequence Modeling
Zhijun Wang
Xuebo Liu
Min Zhang
25
11
0
23 Nov 2022
Helpful Neighbors: Leveraging Neighbors in Geographic Feature
  Pronunciation
Helpful Neighbors: Leveraging Neighbors in Geographic Feature Pronunciation
Llion Jones
R. Sproat
Haruko Ishikawa
Alexander Gutkin
14
1
0
18 Oct 2022
Tree-constrained Pointer Generator with Graph Neural Network Encodings
  for Contextual Speech Recognition
Tree-constrained Pointer Generator with Graph Neural Network Encodings for Contextual Speech Recognition
Guangzhi Sun
C. Zhang
P. Woodland
14
12
0
02 Jul 2022
1