Byte-based Neural Machine Translation
This paper presents experiments comparing character-based and byte-based neural machine translation systems. The main motivation of the byte-based neural machine translation system is to build multi-lingual neural machine translation systems that can share the same vocabulary. We compare the performance of both systems in several language pairs and we see that the performance in test is similar for most language pairs while the training time is slightly reduced in the case of byte-based neural machine translation.
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Language ModelingLanguage ModellingMachine TranslationNamed Entity Recognition (NER)Speech RecognitionTranslationSimilar Papers 제목 키워드 기반
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