Task Dynamics in the Production of American Sign Language

描述（由申请人提供）：拟议的研究旨在开发美国手语（ASL）中符号运动的第一个任务动态模型。该模型将来自运动学标志生产数据的分析。我们的研究方法是建立在发音音系学的理论基础上的，该理论认为语音的基本单位是发音手势。这些手势是从一个生产到另一个不变的运动任务，它们的时间重叠决定了语言输出的结构。在这项研究中，我们假设发音手势也是符号的结构基元，我们试图发现手势是什么，以及它们是如何计时的。在标牌制作过程中，关节必须从一个标牌的位置移动到下一个标牌的位置，并且它们还必须产生单个标牌内部的运动。符号音系学的理论试图区分这两种类型的移动（符号内部和过渡），并确定移动是符号的特定部分，还是仅仅是从一个物理位置到另一个物理位置的手段。本研究将探讨手语中符号内部和过渡运动的运动学和动力学。运动学数据将从本地签名者收集，因为他们产生的迹象与运动朝向或远离身体上的特定位置。签名速度，标志上下文和短语上下文将被操纵，以确定哪些方面的标志生产保持不变时，运动轨迹和速度显式变化。从运动学数据得出的测量结果将被用作计算模型的输入，这将使我们能够检查发音姿势。从计算模型中识别的手势将通过动画程序与人类生产数据进行比较，并由本地ASL签名者判断可理解性和自然性。通过这种方式，我们将使用收敛的证据线来测试符号产生的最小单位是什么以及它们如何相互关联。公共卫生相关性这项研究与NIH的公共卫生使命有关，因为它有助于我们了解美国手语的结构，据估计，北美有50万人使用美国手语。这项研究有可能提高聋人手语使用者的生活质量。我们的方法可以通过自动通信系统为聋人提供更自然的通信方式。如果我们提出的结构准确地描述了符号结构的最小单元，那么它应该为符号合成提供最自然的模型。

DESCRIPTION (provided by applicant): The proposed study seeks to develop the first task-dynamic model of sign movement in American Sign Language (ASL). The model will be derived from analyses of kinematic sign production data. Our approach is grounded in the theory of Articulatory Phonology, which proposes that the basic units of speech are articulatory gestures. These gestures are movement tasks that are invariant from one production to another, and their temporal overlap determines the structure of language output. In this study, we hypothesize that articulatory gestures are also the structural primitives of sign, and we seek to discover what the gestures are and how they are timed. During sign production, the articulators must move from one sign's location to the next sign's location, and they must also produce movements that are internal to an individual sign. Theories of sign phonology have tried to differentiate these two types of movement (sign-internal and transitional) from one another and also to determine whether movement is a specified part of the sign, or simply a means of getting from one physical location to another. This study will examine the kinematics and the dynamics of sign-internal and transitional movements in ASL. Kinematic data will be collected from native signers as they produce signs with movements toward or away from specific locations on the body. Signing speed, sign context, and phrase context will be manipulated in order to identify what aspects of sign production remain invariant when movement trajectories and velocities are explicitly varied. Measures derived from the kinematic data will be used as input to a computational model, which will allow us to examine the articulatory gestures. The gestures that are identified from the computational model will then be compared to human production data via an animation program and judged for intelligibility and naturalness by native ASL signers. In this way, we will use converging lines of evidence to test what the minimal units of sign production are and how they are related to each other. PUBLIC HEALTH RELEVANCE This study is relevant to NIH's public health mission, because it contributes to our understanding of the structure of American Sign Language, which is used by an estimated 500,000 people in North America. The study has the potential to enhance the quality of life for Deaf sign language users. Our approach could lead the way toward a more naturalistic means of communication for Deaf people via automated communication systems. If the structure we have proposed accurately describes the minimal units of sign structure, then it should provide the most natural model for sign synthesis.