Precision and recall of machine translation
2003
226 citations
Machine translation can be evaluated using precision, recall, and the F-measure. These standard measures have significantly higher correlation with human judgments than recently proposed alternatives. More importantly, the standard measures have an intuitive interpretation, which can facilitate insights into how MT systems might be improved. The relevant software is publicly available.
Commonly used evaluation measures including Recall, Precision, F-Measure and\nRand Accuracy are biased and should not be used without clear understanding of\nthe biases, and cor...
Commonly used evaluation measures including Recall, Precision, F-Measure and Rand Accuracy are biased and should not be used without clear understanding of the biases, and corre...
Semantic Textual Similarity (STS) measures the degree of semantic equivalence between two texts. This paper presents the results of the STS pilot task in Semeval. The training d...
Terminological Concept Systems (TCS) provide a means of organizing, structuring and representing domain-specific multilingual information and are important to ensure terminologi...
Recent studies have demonstrated the efficiency of generative pretraining for English natural language understanding. In this work, we extend this approach to multiple languages...
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