USAAR-SHEFFIELD: Semantic Textual Similarity with Deep Regression and Machine Translation Evaluation Metrics

摘要

This paper describes the USAAR-SHEFFIELD systems that participated in the Semantic Textual Similarity (STS) English task of SemEval-2015. We extend the work on using machine translation evaluation metrics in the STS task. Different from previous approaches, we regard the metrics' robustness across different text types and conflate the training data across different subcorpora. In addition, we introduce a novel deep regressor architecture and evaluated its efficiency in the STS task.