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Automatic sign language processing is gaining popularity in Natural LanguageProcessing (NLP) research (Yin et al., 2021). In machine translation (MT) inparticular, sign language translation based on glosses is a prominent approach.In this paper, we review recent works on neural gloss translation. We find thatlimitations of glosses in general and limitations of specific datasets are notdiscussed in a transparent manner and that there is no common standard forevaluation.  To address these issues, we put forward concrete recommendations for futureresearch on gloss translation. Our suggestions advocate awareness of theinherent limitations of gloss-based approaches, realistic datasets, strongerbaselines and convincing evaluation.

Considerations for meaningful sign language machine translation based on glosses