论文标题
基于光泽的有意义的手语机器翻译的注意事项
Considerations for meaningful sign language machine translation based on glosses
论文作者
论文摘要
自动手语处理在自然语言处理（NLP）研究中越来越受欢迎（Yin等，2021）。特别是在机器翻译（MT）中，基于光泽的手语翻译是一种突出的方法。在本文中，我们回顾了有关神经光泽翻译的最新著作。我们发现，通常不会以透明的方式讨论一般光的局限性和特定数据集的局限性，并且没有共同的评估标准。 为了解决这些问题，我们提出了具体建议，以供将来的有关光泽翻译研究。我们的建议提倡对基于光泽的方法，现实数据集，更强的基准和令人信服的评估的固有局限性的认识。
Automatic sign language processing is gaining popularity in Natural Language Processing (NLP) research (Yin et al., 2021). In machine translation (MT) in particular, sign language translation based on glosses is a prominent approach. In this paper, we review recent works on neural gloss translation. We find that limitations of glosses in general and limitations of specific datasets are not discussed in a transparent manner and that there is no common standard for evaluation. To address these issues, we put forward concrete recommendations for future research on gloss translation. Our suggestions advocate awareness of the inherent limitations of gloss-based approaches, realistic datasets, stronger baselines and convincing evaluation.
