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What do post-editors correct? A fine-grained analysis of SMT and NMT errors
2021
Tradumàtica tecnologies de la traducció
The recent improvements in neural MT (NMT) have driven a shift from statistical MT (SMT) to NMT. However, to assess the usefulness of MT models for post-editing (PE) and have a detailed insight of the output they produce, we need to analyse the most frequent errors and how they affect the task. We present a pilot study of a fine-grained analysis of MT errors based on post-editors corrections for an English to Spanish medical text translated with SMT and NMT. We use the MQM taxonomy to compare
doi:10.5565/rev/tradumatica.286
fatcat:725mcpojtnblho4e5atokp7s64