摘要：

Abstract:

【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.