Rule-Based, Neural and LLM Back-Translation: Comparative Insights from a Variant of Ladin
This paper explores the impact of different back-translation approaches on machine translation for Ladin, specifically the Val Badia variant. Given the limited amount of parallel data available for this language (only 18k Ladin-Italian sentence pairs), we investigate the performance of a multilingual neural machine translation model fine-tuned for Ladin-Italian. In addition to the available authentic data, we synthesise further translations by using three different models: a fine-tuned neural model, a rule-based system developed specifically for this language pair, and a large language model. Our experiments show that all approaches achieve comparable translation quality in this low-resource scenario, yet round-trip translations highlight differences in model performance.
Code (0)
등록된 구현이 없습니다.
Tasks
Language ModelingLanguage ModellingLarge Language ModelMachine TranslationSentenceTranslationSimilar Papers 제목 키워드 기반
Balancing Natural Language Processing Accuracy and Normalisation in Extracting Medical Insights
Extracting structured medical insights from unstructured clinical text using Natural Language Processing (NLP) remains an open challenge in healthcare, particularly in non-English contexts where resources are scarce. Thi…
Information ExtractionInformation RetrievalDemystifying Learning of Unsupervised Neural Machine Translation
Unsupervised Neural Machine Translation or UNMT has received great attention in recent years. Though tremendous empirical improvements have been achieved, there still lacks theory-oriented investigation and thus some fun…
Machine TranslationTranslationTranslation vs. Dialogue: A Comparative Analysis of Sequence-to-Sequence Modeling
Understanding neural models is a major topic of interest in the deep learning community. In this paper, we propose to interpret a general neural model comparatively. Specifically, we study the sequence-to-sequence (Seq2S…
Dialogue GenerationMachine TranslationResponse GenerationTranslationLanguage as a matrix product state
We propose a statistical model for natural language that begins by considering language as a monoid, then representing it in complex matrices with a compatible translation invariant probability measure. We interpret the …
TranslationCharacterizing virulence differences in a parasitoid wasp through comparative transcriptomic and proteomic
Background: Two strains of the endoparasitoid Cotesia typhae present a differential parasitism success on the host, Sesamia nonagrioides. One is virulent on both permissive and resistant host populations, and the other o…