Automatic acquisition of lexical formality

Abstract

There has been relatively little work focused on determining the formality level of individual lexical items. This study applies information from large mixedgenre corpora, demonstrating that significant improvement is possible over simple word-length metrics, particularly when multiple sources of information, i.e. word length, word counts, and word association, are integrated. Our best hybrid system reaches 86% accuracy on an English near-synonym formality identification task, and near perfect accuracy when comparing words with extreme formality differences. We also test our word association method in Chinese, a language where word length is not an appropriate metric for formality.