Papers by Seiichiro Kondo
Sentence Concatenation Approach to Data Augmentation for Neural Machine Translation (2021.naacl-srw)
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| Challenge: | Neural machine translation is known to show poor performance at long sentence translations . however, when the sentence length exceeds a certain value, the quality of NMT becomes inferior to that of statistical machine translation. |
| Approach: | They propose a method that uses given parallel corpora as train data to generate long sentences by concatenating two sentences at random. |
| Outcome: | The proposed method improves translation quality more when combined with back-translation. |