Signed languages are the primary means of communication for many deaf and hard of hearing individuals. Since signed languages exhibit all the fundamental linguistic properties of natural language, we believe that tools and theories of Natural Language Processing (NLP) are crucial towards its modeling. However, existing research in Sign Language Processing (SLP) seldom attempt to explore and leverage the linguistic organization of signed languages. This position paper calls on the NLP community to include signed languages as a research area with high social and scientific impact. We first discuss the linguistic properties of signed languages to consider during their modeling. Then, we review the limitations of current SLP models and identify the open challenges to extend NLP to signed languages. Finally, we urge (1) the adoption of an efficient tokenization method; (2) the development of linguistically-informed models; (3) the collection of real-world signed language data; (4) the inclusion of local signed language communities as an active and leading voice in the direction of research.
翻译：手语是许多聋哑人和听力困难人的主要交流手段。由于手语体现了自然语言的所有基本语言特性,我们认为,自然语言处理(NLP)的工具和理论对于其建模至关重要。然而,手语处理(SLP)的现有研究很少试图探索和利用手语处理(SLP)的语言组织。本立场文件呼吁国家语言处理(SLP)社区将手语作为具有高度社会和科学影响的研究领域。我们首先讨论手语的语言语言的语言特性,然后在建模时加以考虑。然后,我们审查目前的SLP模式的局限性,并找出将手语处理(NLP)扩展至手语的公开挑战。最后,我们敦促(1) 采用有效的象征性方法;(2) 开发语言信息化模式;(3) 收集现实世界手语数据;(4) 将当地手语社区纳入研究方向的积极和主导声音。
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