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Kinect-ing the Dots:使用运动捕捉技术来区分手语语言语言和手势表达.

Rose Stamp1, David Cohn, Hagit Hel-Or2

  • 1Department of English Literature and Linguistics, Bar-Ilan University, Israel.

Language and speech
|June 14, 2023
PubMed
概括
此摘要是机器生成的。

运动捕捉技术将手语中的词汇符号与其他表达式 (如构造的动作和分类器构造) 区分开来. 这项研究有助于定义视觉语言中的语言类别"词".

关键词:
标记语言 标记语言是指手语.分类器结构的构造.构建的行动行动构建的行动一个手势,一个手势.语言类别语言类别.移动捕捉是用来捕捉运动的.运动运动运动运动运动运动.

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科学领域:

  • 语言学的语言学.
  • 认知科学 认知科学
  • 运动捕捉技术的技术.

背景情况:

  • 像口语一样,手语的特点是表达的持续流.
  • 将语言单元与其他视觉信号区分开来,对于理解手语结构至关重要.

研究的目的:

  • 在手语中使用动作捕捉来区分词汇符号与构造的动作和分类器构造.
  • 为了研究各种手语表达式类型之间的动态差异.

主要方法:

  • 利用运动捕捉技术,以以色列手语记录和分析运动.
  • 词汇符号的比较动态参数,构造的动作和分类器构造.

主要成果:

  • 与构造的动作和分类器构造相比,词汇符号表现出显著的动力学差异.
  • 动作捕捉可以识别在手语中不同类型的视觉信号的不同的运动模式.

结论:

  • 在手语中,并非所有视觉信号都是语言等价的;它们具有不同的动力学特性.
  • 运动捕捉技术提供了一种方法来定义符号语言中的通用语言类别"词",并将其与表达性手势区分开来.