Ukrainian-to-English folktale corpus: Parallel corpus creation and augmentation for machine translation in low-resource languages
원문 초록
Folktales are linguistically very rich and culturally significant in understanding the source language. Historically, only human translation has been used for translating folklore. Therefore, the number of translated texts is very sparse, which limits access to knowledge about cultural traditions and customs. We have created a new Ukrainian-To-English parallel corpus of familiar Ukrainian folktales based on available English translations and suggested several new ones. We offer a combined domain-specific approach to building and augmenting this corpus, considering the nature of the domain and differences in the purpose of human versus machine translation. Our corpus is word and sentence-aligned, allowing for the best curation of meaning, specifically tailored for use as training data for machine translation models.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Intrinsic vs. Extrinsic Evaluation of Czech Sentence Embeddings: Semantic Relevance Doesn't Help with MT Evaluation
ConECT Dataset: Overcoming Data Scarcity in Context-Aware E-Commerce MT
Building a Functional Machine Translation Corpus for Kpelle
Combining the Best of Both Worlds: A Method for Hybrid NMT and LLM Translation
Same evaluation, more tokens: On the effect of input length for machine translation evaluation using Large Language Models
CycleDistill: Bootstrapping Machine Translation using LLMs with Cyclical Distillation
토론
이 논문과 연결된 포럼 글이 아직 없습니다.