Reranking Hypotheses in Translation Models Using Human Markup

Modern machine translation systems are trained on large volumes of parallel data obtained using heuristic methods of bypassing the Internet. The poor quality of the data leads to systematic translation errors, which can be quite noticeable to humans. To fix such errors, human-based models for rerank...

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Veröffentlicht in:	Journal of computer & systems sciences international 2024-08, Vol.63 (4), p.679-686
Hauptverfasser:	Vorontsov, K. V., Skachkov, N. A.
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial Intelligence Control Engineering Error reduction Heuristic methods Hypotheses Machine translation Mechatronics Robotics
Online-Zugang:	Volltext
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