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The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021 (3)
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Simple Search
Hits 1 – 11 of 11
1
Signed Coreference Resolution ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Yin, Kayo
. - : Underline Science Inc., 2021
BASE
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2
Including Signed Languages in Natural Language Processing ...
Yin, Kayo
;
Moryossef, Amit
;
Hochgesang, Julie
. - : arXiv, 2021
BASE
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3
Including Signed Languages in Natural Language Processing ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Alikhani, Malihe
;
Goldberg, Yoav
. - : Underline Science Inc., 2021
BASE
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4
When Does Translation Require Context? A Data-driven, Multilingual Exploration ...
Yin, Kayo
;
Fernandes, Patrick
;
Martins, André F. T.
. - : arXiv, 2021
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5
Measuring and Increasing Context Usage in Context-Aware Machine Translation ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Fernandes, Patrick
;
Martins, Andre
. - : Underline Science Inc., 2021
BASE
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6
Data Augmentation for Sign Language Gloss Translation ...
Moryossef, Amit
;
Yin, Kayo
;
Neubig, Graham
;
Goldberg, Yoav
. - : arXiv, 2021
Abstract:
Sign language translation (SLT) is often decomposed into video-to-gloss recognition and gloss-to-text translation, where a gloss is a sequence of transcribed spoken-language words in the order in which they are signed. We focus here on gloss-to-text translation, which we treat as a low-resource neural machine translation (NMT) problem. However, unlike traditional low-resource NMT, gloss-to-text translation differs because gloss-text pairs often have a higher lexical overlap and lower syntactic overlap than pairs of spoken languages. We exploit this lexical overlap and handle syntactic divergence by proposing two rule-based heuristics that generate pseudo-parallel gloss-text pairs from monolingual spoken language text. By pre-training on the thus obtained synthetic data, we improve translation from American Sign Language (ASL) to English and German Sign Language (DGS) to German by up to 3.14 and 2.20 BLEU, respectively. ... : 4 pages, 1 page abstract ...
Keyword:
Computation and Language cs.CL
;
FOS Computer and information sciences
URL:
https://arxiv.org/abs/2105.07476
https://dx.doi.org/10.48550/arxiv.2105.07476
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7
Do Context-Aware Translation Models Pay the Right Attention? ...
Yin, Kayo
;
Fernandes, Patrick
;
Pruthi, Danish
. - : arXiv, 2021
BASE
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8
When is Wall a Pared and when a Muro? -- Extracting Rules Governing Lexical Selection ...
Chaudhary, Aditi
;
Yin, Kayo
;
Anastasopoulos, Antonios
. - : arXiv, 2021
BASE
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9
When is Wall a Pared and when a Muro?: Extracting Rules Governing Lexical Selection ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Anastasopoulos, Antonios
;
Chaudhary, Aditi
. - : Underline Science Inc., 2021
BASE
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10
Do Context-Aware Translation Models Pay the Right Attention? ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Chaudhary, Aditi
;
Fernandes, Patrick
. - : Underline Science Inc., 2021
BASE
Show details
11
Better Sign Language Translation with STMC-Transformer ...
Yin, Kayo
;
Read, Jesse
. - : arXiv, 2020
BASE
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