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Neutrosophic Hidden Markov Model for Sign Language Recognition

The Impact of Technological Advancements on the Deaf Community

Have you ever wondered how technology is changing the lives of individuals in the deaf community? In an age when innovation seems limitless, it is critical to investigate how these advancements are improving communication, education, and job opportunities for the deaf community. Let's go over some amazing ways in which technology helps the deaf community

Deafness: Why activists oppose 'oralism', or the use of speech, in deaf education

Deaf education in India still emphasises “oralism”, or the use of speech. But the community argues that sign language is their natural mode of communication.

"Sign language recognition via dimensional global–local shift and cross" by Zihui Guo, Yonghong Hou et al.

Sign languages generally consist of a sequence of upper body gestures and are cooperative processes among various parts such as the hands, arms, and face. Therefore, the dynamics of the parts as well as the holistic appearance of the upper body and individual parts are essential for robust recognition. In this paper, a global–local representation (GLR) module is proposed to boost the spatiotemporal feature modeling. The GLR module is composed of global shift and local shift along the height, width, and temporal dimensions. Specifically, the global shift is applied to the entire feature map for holistic representation, while the local shift restricts itself to local patches to capture detailed features. Furthermore, a novel cross-scale aggregation module is designed to combine the global and local information in different dimensions. Extensive experimental results on three large-scale benchmarks, including WLASL, INCLUDE and LSA64, demonstrate that the proposed method achieves state-o

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