SBIR Phase I: Handheld Devices for Practical Simultaneous Translation

SBIR 第一阶段：用于实用同声翻译的手持设备

• 批准号: 2212978
• 负责人: Drew Penney
• 金额: $ 25.6万
• 依托单位: LEXEL SYNERGETICS, INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-15 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2212978&HistoricalAwards=false
• 关键词: SBIR; Phase; Handheld; Devices; Practical

The broader impact of this Small Business Innovation Research (SBIR) Phase I project on a handheld simultaneous translator advances the state-of-the-art technologies in natural language processing and machine learning acceleration. Beyond technical contributions, the novel translator will likely have a significant impact on a wide range of domains, such as military personnel deployed in foreign countries, businesspeople participating in multilingual meetings, medical service providers, law enforcement, customer support services, diplomats and political representatives, local governmental entities providing services to citizens in the preferred language, and international tourists. As such, the project will have broader impacts in increasing economic competitiveness, advancing health and welfare, and improving military capabilities of the United State. Furthermore, the project helps to enhance equity in education and STEM literacy by enabling better access to educational resources to people of diverse backgrounds, especially immigrants, women, and underrepresented minorities in some countries/regions, who were previously disadvantaged due to limited prior educational access or limited access to foreign language courses.This Small Business Innovation Research (SBIR) Phase I project focuses on the research and development of innovative algorithmic optimizations and a purpose-built translation device to enable fast, accurate and low-power inference for simultaneous translation. The overall approach is to exploit the unspoken but implied connections among language elements at various levels to guide the learning model. Specific techniques are investigated at the phoneme-level, work-level, and sentence-level. Collectively, these innovations aim to reduce the computation complexity of simultaneous translation by orders of magnitude while increasing translation accuracy. A systematic and comprehensive methodology is also being established that allows fast implementation of the inference hardware via high-level synthesis and reports detailed statistics on translation accuracy, latency, power, and area to facilitate a thorough evaluation of the research.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

小企业创新研究 (SBIR) 第一阶段项目对手持式同声翻译机的更广泛影响推动了自然语言处理和机器学习加速领域的最先进技术。除了技术贡献之外，这款新颖的翻译器可能会对广泛的领域产生重大影响，例如部署在外国的军事人员、参加多语言会议的商人、医疗服务提供商、执法、客户支持服务、外交官和政治代表、当地政府实体以首选语言向公民和国际游客提供服务。因此，该项目将对提高美国经济竞争力、促进健康和福利以及提高军事能力产生更广泛的影响。此外，该项目还使不同背景的人们，特别是一些国家/地区的移民、妇女和代表性不足的少数群体，能够更好地获得教育资源，从而有助于提高教育公平和 STEM 素养，这些人以前由于之前的教育机会有限而处于不利地位。这个小型企业创新研究 (SBIR) 第一阶段项目的重点是研究和开发创新算法优化和专用翻译设备，以实现快速、准确和低功耗的同声翻译推理。总体方法是利用不同层次的语言元素之间不言而喻但隐含的联系来指导学习模型。在音素级别、工作级别和句子级别上研究了具体技术。总的来说，这些创新旨在将同声翻译的计算复杂性降低几个数量级，同时提高翻译准确性。系统性、全面的方法论也正在建立中，该方法允许通过高级综合快速实现推理硬件，并报告翻译准确性、延迟、功耗和面积的详细统计数据，以促进对研究的全面评估。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。