Many-to-English Machine Translation Tools, Data, and Pretrained Models
원문 초록
While there are more than 7000 languages in the world, most translation research efforts have targeted a few high-resource languages. Commercial translation systems support only one hundred languages or fewer, and do not make these models available for transfer to low resource languages. In this work, we present useful tools for machine translation research: MTData, NLCodec, and RTG. We demonstrate their usefulness by creating a multilingual neural machine translation model capable of translating from 500 source languages to English. We make this multilingual model readily downloadable and usable as a service, or as a parent model for transfer-learning to even lower-resource languages.
함께 살펴볼 논문
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TASK AWARE MULTI-TASK LEARNING FOR SPEECH TO TEXT TASKS
CycleDistill: Bootstrapping Machine Translation using LLMs with Cyclical Distillation
Gender Bias in English-to-Greek Machine Translation
TACTIC: Translation Agents with Cognitive-Theoretic Interactive Collaboration
Translate With Care: Addressing Gender Bias, Neutrality, and Reasoning in Large Language Model Translations
Should I Share this Translation? Evaluating Quality Feedback for User Reliance on Machine Translation
토론
이 논문과 연결된 포럼 글이 아직 없습니다.