1. METEOR指标 1.1 METEOR简介 METEOR(Metric for Evaluation of Translation with Explicit ORdering)是一种用于评估机器翻译质量的指标,由Banerjee和Lavie在2005年提出。与BLEU不同,METEOR不仅考虑词汇的精确匹配,还引入了同义词、词干和词序等因素,从而提供更全面的评估。 1.2 METEOR的计算方法 METEOR的计算基于以下几...
METEOR: Metric for Evaluation of Translation with Explicit ordered 用于机器翻译的准确性评估,预测集 predictions 和参考集 references 可以是一对一的,也可以是一对多的。 METEOR 使用 单元词组精确度、单元词组召回率、碎片惩罚 三部分的组合来计算分数。 引入了较为灵活的对齐机制。 用通俗的话解释,METEOR 在评估...
1、BLEU 是最早提出的机器翻译评价指标,是所有文本评价指标的源头,怎么吹都不为过。这也是现在机器翻译评价的事实标准,有标准的 perl 测评脚本,这样大家用起来就不会有什么实现上的偏差;Python 实现也很多,我记得 NLTK 工具箱里就有。 BLEU 的大意是比较候选译文和参考译文里的 n-gram(实践中从 unigram 取到 4...
python -m RMS.StartCapture This command will automatically start capturing upon sunset, and stop capturing upon sunrise, do the detection automatically, do the astrometric recalibration (provided an initial astrometric plate was provided), and upload the detections to server. ...
Meteor is not a simple metric and different implementations will create slightly different results.If you want to compare your results to others, use the tool they were using.Theimplementation by Denkowski and Lavieseems to be the one that is used most widely. (Especially don't use NLTK's ...
Some critical software components and algorithms used by our system for the astrometric calibration of the cameras as well as trajectory and orbit solving have been developed by Denis Vida and provided through his RMS (Raspberry Pi Meteor Station) and WMPL (Western Meteor Python Library) open-...