Musicians Show Improved Speech Segregation in Competitive, Multi-Talker Cocktail Party Scenarios

被引:27
|
作者
Bidelman, Gavin M. [1 ,2 ,3 ]
Yoo, Jessica [2 ]
机构
[1] Univ Memphis, Inst Intelligent Syst, Memphis, TN 38152 USA
[2] Univ Memphis, Sch Commun Sci & Disorders, Memphis, TN 38152 USA
[3] Univ Tennessee, Ctr Hlth Sci, Dept Anat & Neurobiol, Memphis, TN 38163 USA
来源
FRONTIERS IN PSYCHOLOGY | 2020年 / 11卷
基金
美国国家卫生研究院;
关键词
acoustic scene analysis; stream segregation; experience-dependent plasticity; musical training; speech-in-noise perception; IN-NOISE PERCEPTION; MUSICAL EXPERIENCE; BRAIN-STEM; ATTENTION; HEARING; REVERBERATION; BILINGUALISM; INTELLIGENCE; PLASTICITY; LISTENERS;
D O I
10.3389/fpsyg.2020.01927
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Studies suggest that long-term music experience enhances the brain's ability to segregate speech from noise. Musicians' "speech-in-noise (SIN) benefit" is based largely on perception from simple figure-ground tasks rather than competitive, multi-talker scenarios that offer realistic spatial cues for segregation and engage binaural processing. We aimed to investigate whether musicians show perceptual advantages in cocktail party speech segregation in a competitive, multi-talker environment. We used the coordinate response measure (CRM) paradigm to measure speech recognition and localization performance in musicians vs. non-musicians in a simulated 3D cocktail party environment conducted in an anechoic chamber. Speech was delivered through a 16-channel speaker array distributed around the horizontal soundfield surrounding the listener. Participants recalled the color, number, and perceived location of target callsign sentences. We manipulated task difficulty by varying the number of additional maskers presented at other spatial locations in the horizontal soundfield (0-1-2-3-4-6-8 multi-talkers). Musicians obtained faster and better speech recognition amidst up to around eight simultaneous talkers and showed less noise-related decline in performance with increasing interferers than their non-musician peers. Correlations revealed associations between listeners' years of musical training and CRM recognition and working memory. However, better working memory correlated with better speech streaming. Basic (QuickSIN) but not more complex (speech streaming) SIN processing was still predicted by music training after controlling for working memory. Our findings confirm a relationship between musicianship and naturalistic cocktail party speech streaming but also suggest that cognitive factors at least partially drive musicians' SIN advantage.
引用
收藏
页数:11
相关论文
共 50 条
  • [41] Continued search for better prediction of aided speech understanding in multi-talker environments
    Xia, Jing
    Kalluri, Sridhar
    Micheyl, Christophe
    Hafter, Ervin
    JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, 2017, 142 (04): : 2386 - 2399
  • [42] Real-Time Speech Recognition in a Multi-talker Reverberated Acoustic Scenario
    Rotili, Rudy
    Principi, Emanuele
    Squartini, Stefano
    Schuller, Bjoern
    ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS: WITH ASPECTS OF ARTIFICIAL INTELLIGENCE, 2012, 6839 : 379 - +
  • [43] Monaural Multi-Talker Speech Recognition with Attention Mechanism and Gated Convolutional Networks
    Chang, Xuankai
    Qian, Yanmin
    Yu, Dong
    19TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2018), VOLS 1-6: SPEECH RESEARCH FOR EMERGING MARKETS IN MULTILINGUAL SOCIETIES, 2018, : 1586 - 1590
  • [44] Target Speaker Verification With Selective Auditory Attention for Single and Multi-Talker Speech
    Xu, Chenglin
    Rao, Wei
    Wu, Jibin
    Li, Haizhou
    IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2021, 29 : 2696 - 2709
  • [45] A microphone array beamforming-based system for multi-talker speech separation
    Hidri, Adel
    Amiri, Hamid
    INTERNATIONAL JOURNAL OF SIGNAL AND IMAGING SYSTEMS ENGINEERING, 2016, 9 (4-5) : 209 - 217
  • [46] Unified Modeling of Multi-Talker Overlapped Speech Recognition and Diarization with a Sidecar Separator
    Meng, Lingwei
    Kang, Jiawen
    Cui, Mingyu
    Wu, Haibin
    Wu, Xixin
    Meng, Helen
    INTERSPEECH 2023, 2023, : 3467 - 3471
  • [47] Smooth GMM based multi-talker spectral conversion for spectrally degraded speech
    Liu, Chuping
    Fu, Qian-Jie
    Narayanan, Shrikanth S.
    2006 IEEE International Conference on Acoustics, Speech and Signal Processing, Vols 1-13, 2006, : 4999 - 5002
  • [48] The cocktail party phenomenon: A review of research on speech intelligibility in multiple-talker conditions
    Bronkhorst, AW
    ACUSTICA, 2000, 86 (01): : 117 - 128
  • [49] STREAMING NOISE CONTEXT AWARE ENHANCEMENT FOR AUTOMATIC SPEECH RECOGNITION IN MULTI-TALKER ENVIRONMENTS
    Caroselli, Joe
    Narayanan, Arun
    Huang, Yiteng
    2022 INTERNATIONAL WORKSHOP ON ACOUSTIC SIGNAL ENHANCEMENT (IWAENC 2022), 2022,
  • [50] The perception of acoustically distorted speech produced with face masks in multilingual multi-talker environments
    Chiu, Faith
    Bartoseviciute, Laura
    Lee, Albert
    Yao, Yujia
    JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, 2023, 153 (03):