Using verbal instructions for route learning: Instruction Analysis
Using verbal instructions for route learning: Instruction Analysis
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使用口头指令进行路线学习：指令分析
DOI：
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发表时间：
2001
期刊：
影响因子：
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通讯作者：
K. Coventry
中科院分区：
文献类型：
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作者：
G. Bugmann;S. Lauria;T. Kyriacou;Ewan Klein;Johan Bos;K. Coventry
未来的家用机器人需要适应用户的特殊需求和环境。用自然语言编程很可能是一种关键方法，使计算机语言幼稚的用户能够指导他们的机器人。本文介绍了基于教学的学习（IBL）系统的设计的初始步骤和考虑。所提出的方法进行测试，在有限的域的路线指示与真实的语音输入和一个真实的移动的机器人使用视觉导航。用户将使用不受约束的语音在一个受限制的特定领域的词汇确定通过分析语料库的路线指示。这将最大限度地提高语音识别性能。机器人将拥有一组适当的原始程序，对应于路线指令中找到的程序。基于96条路线指令，发现任务词汇表包含约270个单词，但不是封闭的。它以每一个新路由指令一个新词的平均速率增加，尽管存在很大的个体间差异。此外，58%的指令不包含词汇表外的单词。发现功能词汇表包括12个不同的过程，并且也不是封闭的。它以平均每25条指令一个新程序的速度增加。
Future domestic robots will need to adapt to the special needs of their users and to their environment. It is likely that programming by natural language will be a key method enabling computer language-naive users to instruct their robots. This paper describes initial steps and considerations towards the design of Instruction-Based Learning (IBL) systems. The proposed methodology is to be tested in the restricted domain of route instructions with real speech input and a real mobile robot using vision for navigation. Users will use unconstrained speech within a restricted domain-specific lexicon determined by analysing a corpus of route instructions. This will maximise speech recognition performance. The robot will possess an appropriate set of primitive procedures that correspond to procedures found in route instructions. Based on 96 route instructions, it is found that the task vocabulary contains approximately 270 words, but is not closed. It increases at an average rate of one new word for every new route instruction, although there are large inter-individual differences. It is also found that 58% of instructions contain no out-of-vocabulary words. The functional vocabulary is found to include 12 different procedures, and is also not closed. It increases at an average rate of one new procedure for every 25 instructions.