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
Hello应助why采纳,获得10
1秒前
1秒前
1秒前
思源应助长青采纳,获得10
1秒前
烟花应助高会和采纳,获得10
2秒前
2秒前
罗坛坛发布了新的文献求助10
5秒前
记海发布了新的文献求助10
6秒前
Jasper应助烟里戏采纳,获得10
6秒前
无000发布了新的文献求助50
6秒前
6秒前
御风善行完成签到,获得积分10
7秒前
许愿胖十斤完成签到,获得积分10
7秒前
7秒前
8秒前
8秒前
CipherSage应助XIA采纳,获得10
8秒前
9秒前
我爱科研789完成签到,获得积分10
9秒前
Toungoo发布了新的文献求助10
9秒前
10秒前
杨建明完成签到,获得积分10
10秒前
10秒前
xixi发布了新的文献求助10
10秒前
背后的日记本完成签到,获得积分10
10秒前
11秒前
李嶍烨发布了新的文献求助30
11秒前
12秒前
袁大头发布了新的文献求助10
13秒前
13秒前
nihaoya完成签到,获得积分10
13秒前
pizwijrit完成签到,获得积分10
13秒前
lzb发布了新的文献求助10
13秒前
duan发布了新的文献求助10
14秒前
14秒前
Yangaaa发布了新的文献求助10
14秒前
14秒前
14秒前
15秒前
HJJHJH发布了新的文献求助30
16秒前
高分求助中
Modern Epidemiology, Fourth Edition 5000
Kinesiophobia : a new view of chronic pain behavior 5000
Molecular Biology of Cancer: Mechanisms, Targets, and Therapeutics 3000
Digital Twins of Advanced Materials Processing 2000
Propeller Design 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
Handbook of pharmaceutical excipients, Ninth edition 1500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 纳米技术 化学工程 生物化学 物理 计算机科学 内科学 复合材料 催化作用 物理化学 光电子学 电极 冶金 细胞生物学 基因
热门帖子
关注 科研通微信公众号,转发送积分 6010932
求助须知:如何正确求助?哪些是违规求助? 7558505
关于积分的说明 16135677
捐赠科研通 5157827
什么是DOI,文献DOI怎么找? 2762499
邀请新用户注册赠送积分活动 1741123
关于科研通互助平台的介绍 1633554