Artificial intelligence in sign language recognition: A comprehensive bibliometric and visual analysis

IF 4 3区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Computers & Electrical Engineering Pub Date : 2024-11-14 DOI:10.1016/j.compeleceng.2024.109854

Yanqiong Zhang , Yu Han , Zhaosong Zhu , Xianwei Jiang , Yudong Zhang

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引用次数: 0

Abstract

Sign language recognition (SLR) plays a crucial role in bridging the communication gap between individuals with hearing impairments and the auditory communities. This study explores the use of artificial intelligence (AI) in SLR through a comprehensive bibliometric analysis of 2,720 articles published from 1988 to 2024. Utilizing tools like VOSviewer and CiteSpace, the research uncovers the landscape of publication outputs, influential articles, leading authors, as well as the intellectual framework of current topics and emerging trends. The findings indicate that since the inception of SLR research in 1988, there has been a rapid expansion in the field, particularly from 2004 onwards. China and India lead in research productivity. Keyword and co-citation analyses highlight that Hidden Markov Model, Kinect, and Deep Learning have been focal points at various stages of SLR development, while transfer learning, Bidirectional Long Short-Term Memory, attention mechanisms, and Transformer models represent recent emerging trends. This research offers valuable insights for scholars and practitioners interested in AI-based SLR.

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手语识别中的人工智能：全面的文献计量学和视觉分析

手语识别（SLR）在缩小听障人士与听觉群体之间的沟通差距方面发挥着至关重要的作用。本研究通过对 1988 年至 2024 年间发表的 2,720 篇文章进行全面的文献计量分析，探讨了人工智能（AI）在手语识别中的应用。研究利用 VOSviewer 和 CiteSpace 等工具，揭示了出版成果、有影响力的文章、主要作者以及当前主题和新兴趋势的知识框架。研究结果表明，自 1988 年开始进行可持续土地管理研究以来，该领域的研究成果迅速增加，尤其是从 2004 年开始。中国和印度的研究生产率遥遥领先。关键词和共同引用分析突出表明，隐马尔可夫模型、Kinect 和深度学习在 SLR 发展的各个阶段都是焦点，而迁移学习、双向长短期记忆、注意机制和 Transformer 模型则代表了近期的新兴趋势。这项研究为对基于人工智能的 SLR 感兴趣的学者和从业人员提供了宝贵的见解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computers & Electrical Engineering 工程技术-工程：电子与电气

CiteScore

9.20

自引率

7.00%

发文量

661

审稿时长

47 days

期刊介绍： The impact of computers has nowhere been more revolutionary than in electrical engineering. The design, analysis, and operation of electrical and electronic systems are now dominated by computers, a transformation that has been motivated by the natural ease of interface between computers and electrical systems, and the promise of spectacular improvements in speed and efficiency. Published since 1973, Computers & Electrical Engineering provides rapid publication of topical research into the integration of computer technology and computational techniques with electrical and electronic systems. The journal publishes papers featuring novel implementations of computers and computational techniques in areas like signal and image processing, high-performance computing, parallel processing, and communications. Special attention will be paid to papers describing innovative architectures, algorithms, and software tools.