自动语音生产的神经动力学
bioRxiv : the preprint server for biology
|February 23, 2026
概括
自动语音涉及广泛的大脑网络,挑战了传统对语音运动皮层的看法. 这项研究揭示了在过度学习的语音任务期间神经控制中的复杂的前和反动态.
科学领域:
- 神经科学是一个神经科学.
- 语音运动控制 语音运动控制
- 计算神经科学是一种神经科学.
背景情况:
- 语音运动皮质对于人类的言语至关重要.
- 传统观点将其作用限制在发音和体感觉上.
- 人们对自动语音处理的理解仍然很差.
研究的目的:
- 在自动语音生成过程中调查神经动力学.
- 检查皮层招募和时间在过度学习的演讲.
- 澄清语音运动皮层在自动语音中的作用.
主要方法:
- 内电皮图 (ECoG) 记录来自左侧皮质.
- 编码模型 (多变量时间响应函数).
- 解码模型 (深度神经网络语音合成).
主要成果:
- 自动语音涉及一个分布式网络 (上,前中心,后中心皮层).
- 观察到减弱的前关节活动和较弱的额头编码.
- 语音运动皮层显示混合的前/反信号,其中一些网站仅供前.
结论:
- 自动语音使用比以前认为的更广泛的皮质网络.
- 语音运动皮层表现出超出纯粹的前控制范围的复杂动态.
- 这些发现重新定义了自动语音处理的时空组织.
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