An Empirical Study on Chinese Character Decomposition in Multiword Expression-Aware Neural Machine Translation

TL;DR

This paper systematically investigates how Chinese character decomposition impacts multi-word expression-aware neural machine translation, addressing unique challenges of Chinese language processing and improving translation quality.

Contribution

It provides the first comprehensive analysis of Chinese character decomposition in MWE-aware NMT, highlighting its benefits for meaning preservation and translation accuracy.

Findings

Chinese character decomposition enhances MWE translation quality

Decomposition improves semantic representation of Chinese words

The approach effectively addresses MWE translation challenges in Chinese

Abstract

Word meaning, representation, and interpretation play fundamental roles in natural language understanding (NLU), natural language processing (NLP), and natural language generation (NLG) tasks. Many of the inherent difficulties in these tasks stem from Multi-word Expressions (MWEs), which complicate the tasks by introducing ambiguity, idiomatic expressions, infrequent usage, and a wide range of variations. Significant effort and substantial progress have been made in addressing the challenging nature of MWEs in Western languages, particularly English. This progress is attributed in part to the well-established research communities and the abundant availability of computational resources. However, the same level of progress is not true for language families such as Chinese and closely related Asian languages, which continue to lag behind in this regard. While sub-word modelling has been successfully applied to many Western languages to address rare words improving phrase comprehension, and enhancing machine translation (MT) through techniques like byte-pair encoding (BPE), it cannot be applied directly to ideograph language scripts like Chinese. In this work, we conduct a systematic study of the Chinese character decomposition technology in the context of MWE-aware neural machine translation (NMT). Furthermore, we report experiments to examine how Chinese character decomposition technology contributes to the representation of the original meanings of Chinese words and characters, and how it can effectively address the challenges of translating MWEs.