迈向一个轻量级的阿拉伯手语手语翻译系统
Mohammed Algabri1,2, Mohamed A Mekhtiche3, Mohamed A Bencherif3
1Computer Science and Information Systems Department, College of Applied Sciences, AlMaarefa University, Riyadh 13713, Saudi Arabia.
Sensors (Basel, Switzerland)
|September 13, 2025
概括
这项研究开发了一种高性能,轻量级的手语翻译系统,用于实时通信. 该系统在 signer-dependent 和 signer-independent 模式中都实现了高精度,简化了聋人和非聋人的沟通.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 自然语言处理自然语言处理.
背景情况:
- 聋人和非聋人之间的有效沟通至关重要.
- 现有的标志到文本系统往往缺乏实时应用程序的性能或效率.
- 沙特手语 (SSL) 数据集对于开发专门的翻译工具至关重要.
研究的目的:
- 为实时应用开发高性能,轻量级的标志到文本翻译系统.
- 用两个沙特手语数据集 (KSU-SSL 和 ArSL) 评估系统的有效性.
- 调查数据集大小 (签字人数和重复次数) 对翻译准确性的影响.
主要方法:
- 实施一个手语翻译模型,以手语依赖模式和手语独立模式进行评估.
- 进行八项实验,以评估各种配置和数据集参数.
- 在模型组件,网络深度和隐藏维度大小上进行全面的废弃研究.
主要成果:
- 该系统在KSU-SSL数据集上在签名者依赖模式下达到97.7%的准确性,在签名者独立模式下达到90.7%.
- 在ArSL数据集上,该模型的准确性达到98.38% (依赖签名者) 和96.22% (独立于签名者).
- 该研究分析了数据集特征和模型架构对性能的影响.
结论:
- 开发的标志到文本系统展示了实时沙特手语翻译的高性能和效率.
- 这些发现突显了数据集大小和签名者可变性在模型培训中的重要性.
- 这项研究有助于通过先进的人工智能提高聋人社区的通信可访问性.
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