The Role of Handling Attributive Nouns in Improving Chinese-To-English Machine Translation
This work addresses a specific grammatical issue in Chinese-to-English machine translation, offering a practical but incremental enhancement for translation systems.
The paper tackled the challenge of translating Chinese attributive nouns to English by creating a dataset with manually inserted particles to fine-tune translation models, resulting in improved handling of this error type.
Translating between languages with drastically different grammatical conventions poses challenges, not just for human interpreters but also for machine translation systems. In this work, we specifically target the translation challenges posed by attributive nouns in Chinese, which frequently cause ambiguities in English translation. By manually inserting the omitted particle X ('DE'). In news article titles from the Penn Chinese Discourse Treebank, we developed a targeted dataset to fine-tune Hugging Face Chinese to English translation models, specifically improving how this critical function word is handled. This focused approach not only complements the broader strategies suggested by previous studies but also offers a practical enhancement by specifically addressing a common error type in Chinese-English translation.