LETRAS: A Learning-based Framework for Machine Translation of Low Resource Languages

LETRAS：基于学习的低资源语言机器翻译框架

• 批准号: 0534217
• 负责人: Jaime Carbonell
• 金额: --
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0534217&HistoricalAwards=false
• 关键词: LETRAS; Learning; based; Framework; Machine

The LETRAS project investigates novel approaches to development of MachineTranslation (MT) technology, with the goal of establishing a general frameworkthat supports building MT prototype systems for languages for which onlylimited amounts of data and resources in electronic form are available. Theresearch focus of the project is on automatic learning of translationtransfer-rules from limited amounts of elicited bilingual data. A new run-timetranslation "engine" maps source language sentences to their target languageequivalents, by building a large structure of possible partial translationsand then applying effective search techniques for recovering the besttranslation. In the last stage, an automatic rule refinement module helps thesystem learn how to correct and improve its imperfect translation rules, basedon feedback on translation errors provided by users. MT prototype systems forseveral language pairs are being constructed as an integral part of theproject and in collaboration with external research groups. The prototypesguide our research and test out our new ideas. At the same time, ourcollaborations with local researchers and native communities promote thedevelopment of information technology for native languages and educate localresearchers with our state-of-the-art MT research. The prototypes include aHebrew-to-English MT system (with University of Haifa, Israel); anInupiaq-to-English MT system (with University of Alaska, Fairbanks, and theInupiat Heritage Center in Barrow, Alaska); and a Karitiana-to-Portuguese MTsystem (with University of Sao Paulo, Brazil). Support for the Alaskacollaboration is being provided by NSF's Office of Polar Programs (OPP), andsupport for the collaborations with Israel and Brazil is being provided byNSF's Office for International Science and Engineering (OISE). OISE is alsoproviding funding for a planning trip to Bolivia to explore a possible Aymara-to-Spanish project. The potential long-term impact of the projectis profound - enabling the development of Machine Translation for manylanguages of the world, which in turn opens the door for active participationof native and minority communities in the information-rich activities of the21st century.

LETRAS项目研究开发机器翻译（MT）技术的新方法，目标是建立一个通用框架，支持为只有有限数量的电子形式数据和资源的语言构建MT原型系统。 该项目的研究重点是从有限的双语数据中自动学习转换规则。一个新的运行时翻译“引擎”将源语言句子映射到它们的目标语言等价物，通过建立一个可能的部分解释的大结构，然后应用有效的搜索技术来恢复最佳翻译。 在最后一个阶段，一个自动规则细化模块帮助翻译公司学习如何纠正和改进其不完善的翻译规则，根据用户提供的翻译错误的反馈。 MT原型系统的几个语言对正在建设作为一个组成部分的项目，并与外部研究小组合作。 原型指导我们的研究并测试我们的新想法。 与此同时，我们与当地研究人员和当地社区的合作促进了母语信息技术的发展，并通过我们最先进的机器翻译研究教育当地研究人员。 这些原型包括希伯来语到英语的机器翻译系统（与以色列海法大学合作）、伊努皮亚语到英语的机器翻译系统（与阿拉斯加大学、费尔班克斯和阿拉斯加巴罗的伊努皮亚文化遗产中心合作）以及卡里蒂亚纳语到葡萄牙语的机器翻译系统（与巴西圣保罗大学合作）。 对阿拉斯加大学的支持由NSF的极地项目办公室（Office of Polar Programs）提供，对与以色列和巴西的合作的支持由NSF的国际科学与工程办公室（Office for International Science and Engineering）提供。 OISE还为计划前往玻利维亚探索可能的艾马拉人到西班牙项目提供资金。 该项目的潜在长期影响是深远的-使世界上多种语言的机器翻译的发展成为可能，这反过来又为土著和少数民族社区积极参与21世纪世纪信息丰富的活动打开了大门。