SGER: Generating Animations of American Sign Language Classifier Predicates

SGER：生成美国手语分类谓词的动画

• 批准号: 0520798
• 负责人: Mitchell Marcus
• 金额: --
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-06-01 至 2006-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0520798&HistoricalAwards=false
• 关键词: SGER; Generating; Animations; American; Sign

American Sign Language (ASL) is a full natural language, with a linguistic structure distinct from English, used as the primary means of communication for approximately one half million deaf people in the United States. Furthermore, because they are unable to hear spoken English during the critical language acquisition years of childhood, the majority of deaf high school graduates in the U.S. have only a fourth grade English reading level. Because of this low English literacy rate and because English and ASL have such different linguistic structure, many deaf people in the United States could benefit from technology that translates English text into animations of ASL performed by a virtual human character on a computer screen. But previous English-to-ASL machine translation projects have made only limited progress. Instead of producing actual ASL animations, these projects have produced restricted subsets of the language, thus allowing them to side-step many important linguistic and animation issues, including in particular the ubiquitous ASL linguistic constructions called "classifier predicates" that are required in order to translate many English input sentences. Classifier predicates are an ASL phenomenon, in which the signer uses the space around his or her body to position invisible objects representing entities or concepts under discussion; the signer's hands show the movement and location of these objects in space. Classifier predicates are the ASL phenomenon that is most unlike elements of spoken or written languages, and they are therefore difficult to translate by machine translation software. In this research the PIs and their graduate students will build on prior research in ASL linguistics, machine translation and artificial intelligence, 3D graphics simulation and human animation, to design and implement a prototype software system capable of producing animations of classifier predicates from English text. In doing so, they will address some of the most challenging issues in English-to-ASL translation, with the goal of producing a software design that can serve as a robust framework for future implementation of a complete English-to-ASL machine translation system. The prototype implementation will have sufficient visual quality and linguistic breadth to enable a pilot evaluation of the design and the quality of the output animations by deaf native ASL signers.Broader Impacts: This research will lead to significant advances in the state of the art relating to English-to-ASL machine translation software, which will eventually allow development of new applications to provide improved access to information, media and services for the hundreds of thousands of deaf Americans who have low English literacy. Instead of displaying English text, devices like computers, closed-captioned televisions, or wireless pagers could show deaf users an animation of a virtual human character performing ASL. Novel educational reading applications software for deaf children to promote English literacy skills could also be developed. The project will also expose the graduate students involved to research issues relating to ASL and animation, and will support a summer ASL language training program at Gallaudet University for these students.

美国手语(ASL)是一种完整的自然语言，其语言结构不同于英语，是美国约50万聋人的主要交流工具。此外，由于他们在童年关键的语言习得阶段听不到英语口语，美国大多数聋人高中毕业生的英语阅读水平只有四年级。由于英语识字率低，而且英语和ASL的语言结构如此不同，美国的许多聋人可以受益于将英语文本翻译成由计算机屏幕上的虚拟人物表演的ASL动画的技术。但之前的英语到ASL机器翻译项目进展有限。这些项目没有制作实际的ASL动画，而是制作了有限的语言子集，从而使它们能够回避许多重要的语言和动画问题，特别是普遍存在的称为“量词谓词”的ASL语言结构，这些结构是翻译许多英语输入句子所必需的。量词谓词是一种ASL现象，在这种现象中，签名者利用他或她身体周围的空间来定位代表所讨论的实体或概念的无形物体；签名者的手显示这些物体在空间中的运动和位置。量词谓词是一种ASL现象，它最不同于口语或书面语的成分，因此很难用机器翻译软件翻译。在这项研究中，PI和他们的研究生将在ASL语言学、机器翻译和人工智能、3D图形模拟和人类动画的先前研究的基础上，设计和实现一个能够从英文文本生成量词谓词动画的原型软件系统。在这样做的过程中，他们将解决英语到ASL翻译中一些最具挑战性的问题，目标是产生一个软件设计，可以作为未来实施完整的英语到ASL机器翻译系统的强有力的框架。原型的实现将具有足够的视觉质量和语言广度，以便能够对聋人本地ASL签名者的设计和输出动画的质量进行试点评估。广泛影响：这项研究将导致与英语到ASL机器翻译软件相关的技术水平的重大进步，最终将允许开发新的应用程序，为数十万英语素养较低的聋人美国人提供更好的信息、媒体和服务。电脑、闭路电视或无线寻呼机等设备可以向聋人用户展示虚拟人物表演ASL的动画，而不是显示英文文本。还可以为聋儿开发新的教育阅读应用软件，以促进英语识字技能。该项目还将使研究生接触到与ASL和动画相关的研究问题，并将支持加拉德特大学为这些学生提供的夏季ASL语言培训计划。