AI突破：脑电波转化为语音助力瘫痪患者发声
加州大学伯克利分校和旧金山分校研究团队开发出革命性AI系统，能够实时将瘫痪患者的脑电波转化为自然语音，且保留患者原声音特征。该技术通过神经义肢采集大脑运动皮层的神经活动，并由AI将其解码为语音，处理延迟仅1秒，较2023年的研究成果缩短了7秒。
系统支持多种脑信号采集设备，包括高密度电极阵列、穿透脑表面的微电极以及非侵入式表面肌电图传感器。研究团队使用患者受伤前的声音样本训练文本到语音模型，通过让患者默读屏幕单词来映射神经活动与语言的关系。
研究人员表示，该技术能显著改善瘫痪及ALS患者的生活质量，未来将致力于加快AI处理速度并使输出语音更具表现力。
UC Berkeley Engineering
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