持续的手语识别及其翻译成语调颜色的语音.
Nurzada Amangeldy1, Aru Ukenova1, Gulmira Bekmanova1
1Faculty of Information Technologies, L.N. Gumilyov Eurasian National University, Astana 010000, Kazakhstan.
Sensors (Basel, Switzerland)
|July 29, 2023
概括
本研究介绍了一种改进的手语识别方法,用于将标志转换成语调的哈萨克文本,用于语音合成. 这项技术旨在提高残疾人的通信可访问性.
科学领域:
- 计算语言学 计算语言学
- 人与计算机的交互
- 语音技术 语言技术
背景情况:
- 将手语转换为文本对于可访问性至关重要.
- 现有的方法缺乏自然语音合成的语调.
- 哈萨克语的语言处理带来了独特的形态和语法挑战.
研究的目的:
- 开发一个改进的连续手语识别系统.
- 将手语识别与哈萨克斯坦自然语言处理器集成为语调.
- 为了使手语短语的语音合成具有准确的语调.
主要方法:
- 连续的手语识别算法.
- 哈萨克人的自然语言处理管道 (形态学,语法,语义学).
- 为简单的哈萨克文句子开发语调模型.
- 模型性能评估的交叉验证.
主要成果:
- 达到0.97.9的平均测试准确度.
- 实现了0.90.9的平均验证准确度.
- 识别了20个不同的哈萨克语句结构与相关的语调模型.
结论:
- 提出的方法有效地将手语转换为语调的哈萨克文本.
- 该系统在识别和语调建模方面表现出高精度.
- 这项技术具有显著的潜力,可以改善聋人和听力障碍者社区的沟通.
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