Revisit Automatic Error Detection for Wrong and Missing Translation -- A Supervised Approach

IJCNLP 2019 Wenqiang LeiWeiwen XuAi Ti AwYuanxin XiangTat Seng Chua

While achieving great fluency, current machine translation (MT) techniques are bottle-necked by adequacy issues. To have a closer study of these issues and accelerate model development, we propose automatic detecting adequacy errors in MT hypothesis for MT model evaluation... (read more)

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