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首页> 外文期刊>Robotics & Machine Learning Daily News >Study Findings from Sri Sivasubramaniya Nadar College of Engineering Provide New Insights into Machine Translation (Sbsim: a Sentence-bert Similarity-based Evaluation Metric for Indian Language Neural Machine Translation Systems)
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Study Findings from Sri Sivasubramaniya Nadar College of Engineering Provide New Insights into Machine Translation (Sbsim: a Sentence-bert Similarity-based Evaluation Metric for Indian Language Neural Machine Translation Systems)

机译:研究结果从斯里兰卡Sivasubramaniya Nadar工程学院提供新的见解机器翻译(Sbsim: Sentence-bert相似性评价指标对印度机器翻译语言神经系统)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Translation have been presented. According to news reporting originating in Tamil Nadu, India, by NewsRx journalists, research stated, “Machine translation (MT) outputs are widely scored using automatic evaluation metrics and human evaluation scores. The automatic evaluation metrics are expected to be easily computable and a reflection of human evaluation.”
机译:机器人技术与新闻记者新闻编辑机器学习每日新闻每日新闻——数据详细的对机器翻译提出了。起源于印度泰米尔纳德邦,NewsRx记者,研究指出,“机器翻译(MT)输出被广泛使用自动评价指标和人类评价分数。将容易可计算和反映人类的评价。”

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