首页语言学
0


从感性的角度学习语言

Learning language from its perceptual context
课程网址: http://videolectures.net/ecmlpkdd08_mooney_llfi/  
主讲教师: Raymond J. Mooney
开课单位: 德克萨斯大学
开课时间: 2008-10-10
课程语种: 英语
中文简介:
目前学习处理自然语言的系统需要费力地构建人工注释的训练数据。理想的情况是, 计算机能够通过在相关但不明确的感知环境中接触语言输入来获得像儿童一样的语言。作为朝着这个方向迈出的一步, 我们提出了一个系统, 学习体育广播模拟机器人足球比赛的例子。训练数据包括关于机器人仿真游戏的文本人工注释。每个注释的一组可能的替代含义将自动从游戏事件跟踪构造。我们以前开发的学习解析和生成自然语言的系统 (krisp 和 wasp) 得到了加强, 以便从这些数据中学习, 然后对新颖的游戏进行评论。该系统的评估的基础上, 它的能力, 解析句子的正确含义, 并产生准确的游戏事件的描述。还对所产生的体育比赛的总体质量进行了人类评价, 并与人工产生的评论进行了比较。
课程简介: Current systems that learn to process natural language require laboriously constructed human-annotated training data. Ideally, a computer would be able to acquire language like a child by being exposed to linguistic input in the context of a relevant but ambiguous perceptual environment. As a step in this direction, we present a system that learns to sportscast simulated robot soccer games by example. The training data consists of textual human commentaries on Robocup simulation games. A set of possible alternative meanings for each comment is automatically constructed from game event traces. Our previously developed systems for learning to parse and generate natural language (KRISP and WASP) were augmented to learn from this data and then commentate novel games. The system is evaluated based on its ability to parse sentences into correct meanings and generate accurate descriptions of game events. Human evaluation was also conducted on the overall quality of the generated sportscasts and compared to human-generated commentaries.
关 键 词: 训练数据; 感性环境; 生成自然语言
课程来源: 视频讲座网
最后编审: 2020-06-08:chenxin
阅读次数: 62