Semantic Knowledge Organization of Basic Gestures in Chinese Sign Language
[Purpose/significance]In order to explore the rich semantic knowledge embedded in sign language corpus and improve the utilization of sign language resources,this study proposes a method for extracting and organizing semantic knowledge from Chinese sign language basic gestures.[Method/process]Firstly,a multimodal feature annotation system for sign language vocabulary is estab-lished and implemented through an annotation scheme.Secondly,basic gestures are extracted by calculating gesture similarity,form-ing clusters of basic gestures and sign language vocabulary.Thirdly,hierarchical clustering is performed on the clusters of basic ges-tures and sign language vocabulary to extract semantic items of basic gestures.Finally,a representation model for basic gesture attri-butes and semantic knowledge is established and stored.[Result/conclusion]Based on the Shanghai sign language vocabulary corpus from the National Sign Language Lexicon,1474 basic gestures are extracted and 4034 semantic items are identified,and a system for basic gesture semantic knowledge is developed.[Innovation/limitation]This study proposes a data-driven method for extracting and organizing the semantic knowledge of basic gestures,and develops a corresponding system platform,providing valuable resource foun-dation for sign language semantic analysis and related fields.The focus of this paper is the semantic knowledge of moneme gestures,without involving the semantic analysis of complex structures such as multi-morpheme gestures and classifying predicates.
Chinese sign languagebasic gesturessemantic knowledgeknowledge extractionknowledge organizationmultimodal
NETL
NSTL
万方数据
