演讲者与听众之间的神经耦合与自然语音的语义和声学特征相关。

Zhuoran Li, Bo Hong, Guido Nolte, Andreas K Engel, Dan Zhang
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引用次数: 0

摘要

最近的研究广泛报道了说话者和听话者在语言交流过程中的脑间神经耦合现象。然而,这种神经耦合背后的具体语音过程仍然难以捉摸。为了弥补这一差距,本研究利用两个脑间数据集,考虑了不同的噪音水平和听者的语言经验(母语与非母语),估计了说话者与听者神经耦合的时间动态与语音特征之间的相关性。我们首先得出了时变的说话者-听者神经耦合,提取了语音的声学特征(包络)和语义特征(熵和惊奇),然后探讨了它们之间的相关关系。我们的研究结果表明,在清晰的条件下,说话者与听者的神经耦合与语义特征相关。然而,随着噪音的增加,这种相关性只对母语听者显著。对于非母语听者,神经耦合主要与声学特征而非语义特征相关。这些结果揭示了在各种情况下,说话者与听者之间的神经耦合如何与声学和语义特征相关联,丰富了我们对自然语音交流过程中脑间神经机制的理解。因此,我们主张更多地关注说话者-听者神经耦合的动态性质及其与多层次语音特征的建模。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Speaker-listener neural coupling correlates with semantic and acoustic features of naturalistic speech.

Recent research has extensively reported the phenomenon of inter-brain neural coupling between speakers and listeners during speech communication. Yet, the specific speech processes underlying this neural coupling remain elusive. To bridge this gap, this study estimated the correlation between the temporal dynamics of speaker-listener neural coupling with speech features, utilizing two inter-brain datasets accounting for different noise levels and listener's language experiences (native vs. non-native). We first derived time-varying speaker-listener neural coupling, extracted acoustic feature (envelope) and semantic features (entropy and surprisal) from speech, and then explored their correlational relationship. Our findings reveal that in clear conditions, speaker-listener neural coupling correlates with semantic features. However, as noise increases, this correlation is only significant for native listeners. For non-native listeners, neural coupling correlates predominantly with acoustic feature rather than semantic features. These results revealed how speaker-listener neural coupling is associated with the acoustic and semantic features under various scenarios, enriching our understanding of the inter-brain neural mechanisms during natural speech communication. We therefore advocate for more attention on the dynamic nature of speaker-listener neural coupling and its modeling with multilevel speech features.

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