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PheMT: A Phenomenon-wise Dataset for Machine Translation Robustness on
  User-Generated Contents

PheMT: A Phenomenon-wise Dataset for Machine Translation Robustness on User-Generated Contents

4 November 2020
Ryoske Fujii
Masato Mita
Kaori Abe
Kazuaki Hanawa
Makoto Morishita
Jun Suzuki
Kentaro Inui
ArXiv (abs)PDFHTML

Papers citing "PheMT: A Phenomenon-wise Dataset for Machine Translation Robustness on User-Generated Contents"

2 / 2 papers shown
Title
Noisy UGC Translation at the Character Level: Revisiting Open-Vocabulary
  Capabilities and Robustness of Char-Based Models
Noisy UGC Translation at the Character Level: Revisiting Open-Vocabulary Capabilities and Robustness of Char-Based Models
José Carlos Rosales Núnez
Guolong Su
Djamé Seddah
56
8
0
24 Oct 2021
Understanding the Impact of UGC Specificities on Translation Quality
Understanding the Impact of UGC Specificities on Translation Quality
José Carlos Rosales Núnez
Djamé Seddah
Guillaume Wisniewski
48
5
0
24 Oct 2021
1