一个基于不同语音模式的多维信号的开放数据集,用务实的普通话语
Ran Zhao1,2, Yanru Bai1,2,3,4, Shuming Zhang1,2
1Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072, China.
Scientific data
|December 8, 2025
概括
这项研究引入了一个新的普通话中文语音数据集,以改善大脑与计算机接口 (BCI) 的沟通,特别是在音调语言和语音障碍语言中.
科学领域:
- 神经科学是一个神经科学.
- 语音技术 语言技术
- 语言学的语言学.
背景情况:
- 语音对于沟通至关重要,但像ALS和中风这样的疾病会损害它.
- 大脑计算机接口 (BCI) 提供了语音恢复的潜力,但面临解码准确性挑战,特别是在音调语言中.
- 现有的语音数据集主要使用印欧语言,限制了对音色语言神经编码的研究.
研究的目的:
- 创建一个全面的,开放的多式联络数据集,用于普通话中文语音.
- 促进对音色语言神经编码的研究.
- 推进辅助通信技术和神经语音解码.
主要方法:
- 收集了30名受试者的多式联络信号 (EEG,sEMG,语音).
- 包括普通话中文的公开,静音和想象式语音模式.
- 为语音处理研究开发了一个全面的开放数据集.
主要成果:
- 建立了一个有价值的数据集,用于探索音色语言的神经动态.
- 为普通话汉语使用者改善BCI提供了基础.
- 支持跨语言语音处理和数据驱动的BCI创新.
结论:
- 新的数据集对于理解大脑中音调语言处理至关重要.
- 它将加强更准确和更具包容性的辅助通信技术的发展.
- 这个资源为各种语言背景的神经语音解码带来了进步.
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