从分布式语言网络中解码自然主义连续语音的发音和语音组件
Tessy M Thomas1,2, Aditya Singh1,2, Latané P Bullock1,2
1Vivian L. Smith Department of Neurosurgery, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, United States of America.
Journal of neural engineering
|July 24, 2023
概括
立体电脑学 (sEEG) 允许从广泛的大脑活动中解码语音组件,为语音大脑-计算机接口 (语音-BCI) 提供了新的目标.
科学领域:
- 神经科学是一个神经科学.
- 语音科学 语言科学
- 生物医学工程 生物医学工程
背景情况:
- 语音的产生涉及到一个分布式的大脑网络.
- 当前的语音-大脑-计算机接口 (语音-BCI) 往往专注于有限的表面大脑区域.
- 立体电脑电图 (sEEG) 提供了一种侵入性较小的方法来访问分布式大脑活动.
研究的目的:
- 调查sEEG对从广泛的皮层部位解读语音组件的潜力.
- 在连续语音生产中识别表达和语音组件的神经相关物.
- 探索用于高级语音BCI开发的新型神经点.
主要方法:
- 使用立体电脑电图 (sEEG) 来记录八名参与者的神经活动在连续发言过程中 (大声阅读).
- 在宽带马活动上训练有素的线性分类器来解码发音组件 (发音位置/方式) 和语音.
- 员工嵌套五倍交叉验证以评估解码性能.
主要成果:
- 实现了对口音位置 (18.7%),口音方式 (26.5%) 和语音 (4.81%) 的分类准确度.
- 最高的准确率达到26.3% (地点),35.7% (方式) 和9.88% (语音).
- 有效的解码电极分布在多个大脑区域,包括感觉运动,额叶,叶和状皮层,表明神经表征广泛存在.
结论:
- 语音组件在分布式皮质网络中表示,而不是局部化到单一区域.
- 通过微创伤技术,sEEG使连续语音组件的解码成为可能.
- 这些发现为语言神经生物学提供了关键的见解,并为未来的语音BCI确定了有希望的神经点.
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