关于机器学习翻译的指标或评估
Metrics or evaluation about machine learning translation
你们能推荐一些关于翻译机器学习的评估或指标吗：例如日语到英语等。如果可能的话，你能告诉我一些关于指标的论文吗？我是翻译新手。谢谢！
尽管以 this 2006 article, BLEU (BiLingual Evaluation Understudy) score is still the most commonly used metric for machine translation. According to the Wikipedia page、
开头的批评和争论不断
BLEU is an algorithm for evaluating the quality of text which has been machine-translated from one natural language to another. Quality is considered to be the correspondence between a machine's output and that of a human: "the closer a machine translation is to a professional human translation, the better it is" – this is the central idea behind BLEU. BLEU was one of the first metrics to achieve a high correlation with human judgements of quality, and remains one of the most popular automated and inexpensive metrics.
更具体地说，如果你想看日英翻译，有一个class project from Stanford CS 224d用神经网络技术将简单的日语句子如「彼女は敌だった」翻译成英语，并使用BLEU作为评价指标。
如果您想阅读更多有关机器翻译的资料，我建议您从最近最有影响力的一本开始，即 Neural machine translation by jointly learning to align and translate by Yoshua Bengio et al. You can also look at the top papers that cited the BLEU critics 以了解其他常用指标。
你们能推荐一些关于翻译机器学习的评估或指标吗：例如日语到英语等。如果可能的话，你能告诉我一些关于指标的论文吗？我是翻译新手。谢谢！
尽管以 this 2006 article, BLEU (BiLingual Evaluation Understudy) score is still the most commonly used metric for machine translation. According to the Wikipedia page、
开头的批评和争论不断BLEU is an algorithm for evaluating the quality of text which has been machine-translated from one natural language to another. Quality is considered to be the correspondence between a machine's output and that of a human: "the closer a machine translation is to a professional human translation, the better it is" – this is the central idea behind BLEU. BLEU was one of the first metrics to achieve a high correlation with human judgements of quality, and remains one of the most popular automated and inexpensive metrics.
更具体地说，如果你想看日英翻译，有一个class project from Stanford CS 224d用神经网络技术将简单的日语句子如「彼女は敌だった」翻译成英语，并使用BLEU作为评价指标。
如果您想阅读更多有关机器翻译的资料，我建议您从最近最有影响力的一本开始，即 Neural machine translation by jointly learning to align and translate by Yoshua Bengio et al. You can also look at the top papers that cited the BLEU critics 以了解其他常用指标。