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English(EN) Decoding Naturalistic Speech from fMRI with Temporal Modeling and Multimodal Alignment

新型解码器可从fMRI大脑活动中重建语音

研究人员开发了一种名为NOEMA的新型时间卷积解码器,用于从功能性磁共振成像(fMRI)数据中重建感知到的语音。该解码器将fMRI测量窗口与多模态刺激嵌入对齐,这些嵌入结合了文本、音频和语音表示。在从大脑活动中检索正确语音片段方面,NOEMA比基线解码器有了显著改进,在两个自然语言语音数据集的42%以上的查询中,能在2000个候选片段中将正确片段排在前10位。 AI

影响 这项研究提高了从神经数据中解码语音感知等复杂认知过程的能力,可能对脑机接口和认知神经科学产生影响。

排序理由 该集群包含一篇详细介绍解码大脑活动新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新型解码器可从fMRI大脑活动中重建语音

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该集群包含一篇详细介绍解码大脑活动新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Corentin Caris, Louis Jalouzot, Nona Rajabi, G\'eraud Ilinca, Ahmed Hassayoune, Asilbek Muminov, Thadd\'ee Delebarre, Clara Fonteneau, Charles Maussion, Bertrand Thirion, Alexis Thual, Antoine Collas ·

    利用时间建模和多模态对齐解码功能性磁共振成像中的自然语言语音

    arXiv:2610.22049v1 Announce Type: cross Abstract: Reconstructing what a person perceives from their brain activity is a stringent test of whether neural recordings carry meaningful information. Naturalistic speech offers a rich testbed for this challenge: it unfolds over multiple…