He Xiaomin, Raghavan Vinay S, Mesgarani Nima
Department of Electrical Engineering, Columbia University, New York, NY, USA.
Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA.
bioRxiv. 2024 Oct 12:2024.10.10.616515. doi: 10.1101/2024.10.10.616515.
Robust neural encoding of speech in noise is influenced by several factors, including signal-to-noise ratio (SNR), speech intelligibility (SI), and attentional effort (AE). Yet, the interaction and distinct role of these factors remain unclear. In this study, fourteen native English speakers performed selective speech listening tasks at various SNR levels while EEG responses were recorded. Attentional performance was assessed using a repeated word detection task, and attentional effort was inferred from subjects' gaze velocity. Results indicate that both SNR and SI enhance neural tracking of target speech, with distinct effects influenced by the previously overlooked role of attentional effort. Specifically, at high levels of SI, increasing SNR leads to reduced attentional effort, which in turn decreases neural speech tracking. Our findings highlight the importance of differentiating the roles of SNR, SI, and AE in neural speech processing and advance our understanding of how noisy speech is processed in the auditory pathway.
噪声环境中语音的稳健神经编码受多个因素影响,包括信噪比(SNR)、语音可懂度(SI)和注意力投入(AE)。然而,这些因素之间的相互作用及各自独特作用仍不明确。在本研究中,14名以英语为母语的受试者在不同信噪比水平下执行选择性语音聆听任务,同时记录脑电图反应。使用重复单词检测任务评估注意力表现,并根据受试者的注视速度推断注意力投入。结果表明,信噪比和语音可懂度均增强了对目标语音的神经追踪,且存在受此前被忽视的注意力投入作用影响的不同效应。具体而言,在高语音可懂度水平下,增加信噪比会导致注意力投入减少,进而降低神经语音追踪。我们的研究结果凸显了区分信噪比、语音可懂度和注意力投入在神经语音处理中作用的重要性,并推动了我们对听觉通路中噪声语音处理方式的理解。