积极倾听
言语感知
计算机科学
选择性听觉注意
感知
清晰
语音识别
解码方法
忠诚
心理学
脑电图
听觉感知
听觉系统
听觉皮层
听力损失
钥匙(锁)
听力学
水准点(测量)
认知心理学
高保真
神经计算语音处理
语音处理
噪音(视频)
作者
Vishal Choudhari,Maximilian Nentwich,Sarah Johnson,Jose L. Herrero,Stephan Bickel,Ashesh D. Mehta,Daniel Friedman,Adeen Flinker,Edward F. Chang,Nima Mesgarani
标识
DOI:10.1038/s41593-026-02281-5
摘要
Understanding speech in noisy environments is difficult for many people, and current hearing aids often fail because they amplify all sounds rather than the talker of interest. Auditory attention decoding (AAD) offers a potential solution by using the listener’s brain signals to identify and enhance the attended speaker, but it has been unclear whether this can provide real-time perceptual benefits. Here we used high-resolution intracranial electroencephalography in patients undergoing neurosurgical procedures to implement a closed-loop system that achieves the decoding fidelity necessary to dynamically amplify the attended talker. Across multiple experiments, the system improved speech intelligibility, reduced listening effort and was consistently preferred by subjects. It also tracked both instructed and self-initiated attention shifts. By providing direct evidence that a real-time, brain-controlled hearing system can enhance perception, this work establishes a key performance benchmark for future auditory brain–computer interfaces and advances AAD from a theoretical concept to a validated solution for personalized assistive hearing. This study shows that brain signals can identify and amplify the voice a person wants to hear in a crowded scene. Choudhari et al. provide evidence that brain-controlled hearing can improve speech perception and clarity in noisy environments.
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