一种高性能神经假体用于语音解码和形象控制
Sean L Metzger1,2,3, Kaylo T Littlejohn1,2,4, Alexander B Silva1,2,3
1Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA.
Nature
|August 23, 2023
概括
这项研究开发了一种脑电脑接口, 它将无声语音解码为文字,音频和化身动画,
科学领域:
- 神经科学
- 生物医学工程
- 人工智能
背景情况:
- 恢复患者的沟通是一项重大挑战.
- 现有的语音神经假体往往缺乏自然的速度和表现力.
- 严重的肢体和声音严重限制了沟通能力.
研究的目的:
- 开发一个高性能,实时的语音神经假体.
- 为了实现多式联络输出 (文字,语音,面部动画).
- 恢复严重的人体沟通.
主要方法:
- 语音皮层的高密度表面电皮图 (ECoG) 记录.
- 深度学习模型是从试图默默说话的神经数据中训练出来的.
- 在实时解码文本,合成语音和化身动画模式.
主要成果:
- 实现了快速,大词汇的文本解码,每分钟78个单词,字错误率为25%.
- 演示了可理解和个性化的语音合成, 与受伤前的参与者的声音相匹配.
- 启用面部形象动画控制语音和非语音手势.
- 在训练两周内获得高解码性能.
结论:
- 一种多模式的语音神经假肢方法显示出恢复沟通的巨大潜力.
- 这项技术可以为患有严重的人提供完整的体现性沟通.
- 快速训练和高性能表明大脑-计算机接口的临床可行性.
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