FBK: Combining Machine Translation Evaluation and Word Similarity metrics for Semantic Textual Similarity

This paper describes the participation of FBK in the Semantic Textual Similarity (STS) task organized within Semeval 2012. Our approach explores lexical, syntactic and semantic machine translation evaluation metrics combined with distributional and knowledgebased word similarity metrics. Our best model achieves 60.77% correlation with human judgements (Mean score) and ranked 20 out of 88 submitted runs in the Mean ranking, where the average correlation across all the sub-portions of the test set is considered.