• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Annals of the New York Academy of Sciences >The Contribution of Local Features to Familiarity Judgments in Music
【24h】

The Contribution of Local Features to Familiarity Judgments in Music

机译：地方特色对音乐熟悉程度判断的贡献

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The contributions of local and global features to object identification depend upon the context. For example, while local features play an essential role in identification of words and objects, the global features are more influential in face recognition. In order to evaluate the respective strengths of local and global features for face recognition, researchers usually ask participants to recognize human faces (famous or learned) in normal and scrambled pictures. In this paper, we address a similar issue in music. We present the results of an experiment in which musically untrained participants were asked to differentiate famous from unknown musical excerpts that were presented in normal or scrambled ways. Manipulating the size of the temporal window on which the scrambling procedure was applied allowed us to evaluate the minimal length of time necessary for participants to make a familiarity judgment. Quite surprisingly, the minimum duration for differentiation of famous from unknown pieces is extremely short. This finding highlights the contribution of very local features to music memory.
机译：局部和全局特征对对象识别的贡献取决于上下文。例如，尽管局部特征在识别单词和对象中起着至关重要的作用，但是全局特征在面部识别中的影响更大。为了评估面部识别的局部和全局特征各自的优势，研究人员通常要求参与者在正常和混乱的图像中识别人脸（著名的或博学的）。在本文中，我们解决了音乐中的类似问题。我们介绍了一项实验的结果，其中，未经音乐训练的参与者被要求区分以正常或加扰方式呈现的著名音乐片段与未知音乐片段。通过操纵加扰程序的时间窗口的大小，我们可以评估参与者做出熟悉判断所需的最短时间。令人惊讶的是，区分著名作品和未知作品的最短时间非常短。这一发现突出了非常本地化功能对音乐记忆的贡献。

著录项

  • 来源
    《Annals of the New York Academy of Sciences》 |2009年第2009期|234-244|共11页
  • 作者

    Emmanuel Bigand; Yannick Gerard; Paul Molin;

  • 作者单位

    EEAD-CNRS UMR 5022, Universite de Bourgogne, 2, Esplanade Erasme, Pole AAFE. Universite de Bourgogne. F-21000 Dijon, France;

    LEAD-CNRS, Universite de Bourgogne, Institut Universitaire de France, Dijon, France;

    LEAD-CNRS, Universite de Bourgogne, Institut Universitaire de France, Dijon, France;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    music; memory; local features;

    机译：音乐;记忆;地方特色;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号