EAGER: Simplification as Machine Translation

EAGER：简化为机器翻译

• 批准号: 1430651
• 负责人: Chris Callison-Burch
• 金额: $ 9.97万
• 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: 2014
• 资助国家: 美国
• 起止时间: 2014-05-01 至 2016-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1430651&HistoricalAwards=false
• 关键词: EAGER; Simplification; Machine; Translation

This EArly Grant for Exploratory Research aims to advance the text simplification technology that automatically rewrites complex English texts into simpler English texts. Research into this topic has many potential practical applications. It can provide reading aids for people with disabilities, low-literacy, non-native backgrounds or non-expert knowledge. It can also help with many other computer technologies that need to process difficult words and complicated sentences. This one-year exploratory project focuses on simplification for children with different reading levels. If this technology is successful, it could help make knowledge accessible to all children and gradually help to improve their reading skills.Simplification can be thought of as a monolingual translation task, where the output is equivalent in meaning to the input, but its surface form is constrained by a readability or grade-level requirement. Prior work has drawn the connection between machine translation and text simplification, but has treated the SMT technology as a black box. Going beyond previous work, this study provides an extensive exploration of adapting key parts of the statistical machine translation pipeline to simplify text. It aims to tailor simplification to different readability levels. The three research activities being undertaken in this study are: (1) constructing a "parallel corpus" consisting of complex sentence paired with several different levels of simplification, (2) developing automatic metrics for targeted simplification, and (3) designing features for targeted simplification.

EArly探索性研究基金旨在推进文本简化技术，将复杂的英语文本自动重写为更简单的英语文本。对这一主题的研究有许多潜在的实际应用。它可以为残疾人、低识字率、非本地背景或非专业知识的人提供阅读辅助。它还可以帮助许多其他需要处理困难单词和复杂句子的计算机技术。这个为期一年的探索性项目的重点是简化不同阅读水平的儿童。如果这项技术获得成功，它将有助于让所有儿童都能接触到知识，并逐步帮助提高他们的阅读技能。简化可以被认为是一项单语翻译任务，输出的内容与输入的内容在意义上是相同的，但其表面形式受到可读性或年级要求的限制。先前的工作已经在机器翻译和文本简化之间建立了联系，但将SMT技术视为黑盒。超越以前的工作，这项研究提供了一个广泛的探索，适应统计机器翻译管道的关键部分，以简化文本。 它的目的是根据不同的可读性水平来定制简化。本研究的三项研究活动是：（1）构建一个由复杂句子和几个不同程度的简化组成的“平行语料库”，（2）开发针对性简化的自动度量，（3）设计针对性简化的特征。