Semantically Informed Slang Interpretation

TL;DR

This paper introduces a semantically informed framework for interpreting slang that combines context and semantic appropriateness, achieving state-of-the-art accuracy and enabling improved translation of informal language.

Contribution

It presents a novel SSI framework that jointly considers context and semantics for slang interpretation, outperforming existing methods and applicable to translation tasks.

Findings

Achieves state-of-the-art accuracy in slang interpretation

Effective in zero-shot and few-shot learning scenarios

Enhances machine translation of slang from English to other languages

Abstract

Slang is a predominant form of informal language making flexible and extended use of words that is notoriously hard for natural language processing systems to interpret. Existing approaches to slang interpretation tend to rely on context but ignore semantic extensions common in slang word usage. We propose a semantically informed slang interpretation (SSI) framework that considers jointly the contextual and semantic appropriateness of a candidate interpretation for a query slang. We perform rigorous evaluation on two large-scale online slang dictionaries and show that our approach not only achieves state-of-the-art accuracy for slang interpretation in English, but also does so in zero-shot and few-shot scenarios where training data is sparse. Furthermore, we show how the same framework can be applied to enhancing machine translation of slang from English to other languages. Our work creates opportunities for the automated interpretation and translation of informal language.