Using Speech Recognition to Enhance Communication Capabilities for Individuals with Physical Disabilities

使用语音识别增强身体残障人士的沟通能力

• 批准号: 0328391
• 负责人: Andrew Sears
• 金额: --
• 依托单位: University of Maryland Baltimore County
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-15 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0328391&HistoricalAwards=false
• 关键词: Using; Speech; Recognition; Enhance; Communication

This project builds on the PI's previous efforts, placing a special emphasis on communications-oriented activities and individuals with physical disabilities. The research will focus on improving user interaction with speech recognition systems. Previously, the PI developed a novel error specification technique that uses confidence scores to facilitate the recognition error correction process. While earlier efforts by others to use confidence scores for this purpose had largely been unsuccessful, the PI's initial evaluation of his technique has yielded promising results; whereas earlier efforts relied on identifying specific words that were incorrect, the PI's technique can prove beneficial even if it is only possible to identify the regions where errors may exist. In the new project, the PI will integrate confidence scores with techniques from natural language processing, to facilitate the process of correcting recognition errors. He will develop novel interaction techniques and models, that support new interaction scenarios and allow for better understanding of the relationship between users and speech recognition systems. Questions to be addressed include the following: Can we expand existing models to effectively describe interactions between users and speech recognition systems when error correction activities are explicitly separated from dictation? How can we support the process of finding and correcting recognition errors when these activities are temporally separated from dictation? How do the abilities and limitations of individuals (e.g., traditional users and individuals with various disabilities) affect their strategies when completing tasks that involve deferred error correction?Broader Impacts: This research extends an existing collaboration between UMBC's Information Systems Department and the Workforce and Technology Center (WTC). Speech recognition can be a critical technology for individuals with physical disabilities. While these individuals have been shown to employ different strategies as compared to traditional computer users, limited research has focused on the use of speech recognition technologies by this important group of potential users. Therefore, by explicitly investigating the challenges these individuals encounter when using speech recognition technologies, this project will directly impact this underrepresented group of users, and will furthermore facilitate greater independence and new employment opportunities for them. Because a broad range of users will be included in this project, the results will also benefit traditional computer users with no physical disabilities. Through the collaboration with the WTC, the PI will distribute his results via appropriate publications within the rehabilitation community, in addition to the HCI and ASR communities.

该项目以 PI 之前的工作为基础，特别强调以沟通为导向的活动和身体残疾的个人。 该研究将侧重于改善用户与语音识别系统的交互。 此前，PI 开发了一种新颖的错误规范技术，该技术使用置信度分数来促进识别错误纠正过程。 虽然其他人早期使用置信度分数来实现此目的的努力基本上不成功，但 PI 对他的技术的初步评估已经产生了有希望的结果；虽然早期的工作依赖于识别不正确的特定单词，但 PI 的技术即使只能识别可能存在错误的区域，也可以证明是有益的。 在新项目中，PI 将把置信度分数与自然语言处理技术相结合，以促进纠正识别错误的过程。 他将开发新颖的交互技术和模型，支持新的交互场景，并更好地理解用户和语音识别系统之间的关系。 要解决的问题包括：当纠错活动与听写明确分开时，我们能否扩展现有模型以有效地描述用户和语音识别系统之间的交互？ 当这些活动暂时与听写分开时，我们如何支持发现和纠正识别错误的过程？ 个人（例如，传统用户和患有各种残疾的个人）的能力和限制如何影响他们在完成涉及延迟纠错的任务时的策略？更广泛的影响：这项研究扩展了 UMBC 信息系统部门与劳动力和技术中心 (WTC) 之间的现有合作。 对于身体残疾的人来说，语音识别可能是一项关键技术。 虽然这些人与传统计算机用户相比已被证明采用了不同的策略，但有限的研究集中在这一重要潜在用户群体对语音识别技术的使用上。因此，通过明确调查这些人在使用语音识别技术时遇到的挑战，该项目将直接影响这一未被充分代表的用户群体，并将进一步为他们提供更大的独立性和新的就业机会。 由于该项目将包含广泛的用户，因此其结果也将使没有身体残疾的传统计算机用户受益。通过与 WTC 的合作，除了 HCI 和 ASR 社区之外，PI 将通过康复社区内的适当出版物发布其结果。