Cognitive computing on Chinese Sign Language perception and comprehension

Yao, Dengfeng; Jiang, Minghu; Abulizi, Abudoukelimu; Li, Hanjing

doi:10.1109/icci-cc.2015.7259370

Cited by 1 publication

(2 citation statements)

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“…Hierarchical structure. Low-level areas in the hierarchy generate specific information that increases speed and contain further details, whereas high-level areas form stable spatial invariance, change slowly, and show high-level semantic object expression (Adapted from Yao et al, 2015) In SL communication, both substantial and semantic information (substantial information includes hand shape, hand location, hand movement, hand orientation, head tilting, shoulder tilting, eye gazing, body gestures, and facial expressions, and semantic information is represented into semantic concepts by these substantial SL information) almost exclusively relies on signs. However, accurate SL information analysis and prediction remain as challenging tasks in the field of natural SL processing.…”

Section: Semantic Network Model (Snm)mentioning

confidence: 99%

“…Judgment refers to the process in which the perceived information or the information stored in memory is compared, matched, or classified, and a decision or prediction is made. After the spreading activation, the network records the attention features of users and activates their future preferences (Yao et al, 2015) Concepts are in the form of network storage. The different concepts are stored in different functional areas in both hemispheres of the human brain.…”

Section: Figure 2 Sl Comprehension Frame Based On the Pmj Principle P...mentioning

confidence: 99%

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Semantic Network Model for Sign Language Comprehension

Kang

Yao

Jiang

et al. 2022

International Journal of Cognitive Informatics and Natural Intelligence

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In this study, the authors propose a computational cognitive model for sign language (SL) perception and comprehension with detailed algorithmic descriptions based on cognitive functionalities in human language processing. The semantic network model (SNM) that represents semantic relations between concepts is used as a form of knowledge representation. The proposed model is applied in the comprehension of sign language for classifier predicates. The spreading activation search method is initiated by labeling a set of source nodes (e.g., concepts in the semantic network) with weights or “activation” and then iteratively propagating or “spreading” that activation out to other nodes linked to the source nodes. The results demonstrate that the proposed search method improves the performance of sign language comprehension in the SNM.

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Section: Semantic Network Model (Snm)mentioning

confidence: 99%

Section: Figure 2 Sl Comprehension Frame Based On the Pmj Principle P...mentioning

confidence: 99%