Speaker-listener neural coupling correlates with semantic and acoustic features of naturalistic speech

语音识别 人工神经网络 意识的神经相关物 心理学 计算机科学 特征(语言学) 联轴节(管道) 人工智能 认知 语言学 神经科学 机械工程 工程类 哲学
作者
Zhuoran Li,Bo Hong,Guido Nolte,Andreas K. Engel,Dan Zhang
出处
期刊:Social Cognitive and Affective Neuroscience [Oxford University Press]
标识
DOI:10.1093/scan/nsae051
摘要

Abstract Recent research has extensively reported the phenomenon of inter-brain neural coupling between speaker and listener 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 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 modelling with multi-level speech features.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
我是老大应助活力的驳采纳,获得10
1秒前
充电宝应助唠叨的安荷采纳,获得10
1秒前
日辰彗心完成签到 ,获得积分10
1秒前
1秒前
houbin发布了新的文献求助10
2秒前
3秒前
3秒前
英俊的铭应助豪豪采纳,获得10
3秒前
4秒前
4秒前
4秒前
热河发布了新的文献求助10
4秒前
4秒前
hyperle完成签到,获得积分10
6秒前
zyl发布了新的文献求助10
6秒前
万能图书馆应助tx采纳,获得10
6秒前
核桃发布了新的文献求助10
7秒前
百里怡发布了新的文献求助10
7秒前
7秒前
7秒前
张土豆发布了新的文献求助30
8秒前
张静怡发布了新的文献求助10
8秒前
路lu发布了新的文献求助10
9秒前
9秒前
勤恳的语蝶完成签到 ,获得积分10
10秒前
10秒前
勤恳的箴完成签到,获得积分10
10秒前
天天快乐应助dean采纳,获得10
11秒前
上官若男应助科研通管家采纳,获得10
11秒前
脑洞疼应助科研通管家采纳,获得10
11秒前
李爱国应助科研通管家采纳,获得10
11秒前
大个应助科研通管家采纳,获得10
11秒前
11秒前
11秒前
科研狗应助科研通管家采纳,获得50
12秒前
上官若男应助科研通管家采纳,获得10
12秒前
12秒前
12秒前
无花果应助科研通管家采纳,获得10
12秒前
搜集达人应助科研通管家采纳,获得10
12秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Modern Epidemiology, Fourth Edition 5000
Digital Twins of Advanced Materials Processing 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
Polymorphism and polytypism in crystals 1000
Signals, Systems, and Signal Processing 610
Discrete-Time Signals and Systems 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6024491
求助须知:如何正确求助?哪些是违规求助? 7656750
关于积分的说明 16176485
捐赠科研通 5172859
什么是DOI,文献DOI怎么找? 2767757
邀请新用户注册赠送积分活动 1751236
关于科研通互助平台的介绍 1637502