首页> 外文会议>International Conference on Electrical Engineering and Informatics >Indonesian natural voice command for robotic applications
【24h】

Indonesian natural voice command for robotic applications

机译:机器人应用的印度尼西亚自然语音命令

获取原文
获取外文期刊封面目录资料

摘要

Human-machine interaction has been growing with the discovery of artificial intelligence technology. The development of human-machine interaction leads to a more natural interaction. In daily interactions, human uses speech, more dominant than the other way such as gestures and eye contact. Speech is the vocalized form of human communication which is closely related to language system. The problem is meaning, ambiguity, and the language that is not according to the rules of syntax, causing the command translation become more complex. To understand the meaning of the voice command, it is necessary to know the semantic and syntactic structure of sentences. An artificial intelligence technology that can understand Indonesian voice commands for robotic applications will be developed in this research. The purpose of this research is to translate voice command into the robots action, to generate human-machine interaction more natural. The voice command will be extracted using bark-frequency cepstral coefficients. Cepstral identified into words using neural networks. Words in a complete sentences will be processed using natural language processing so that, the meaning and appropriate action from the given command can be executed. Speech recognition experiments with 28 sets of speech signal obtain 82 % accuracy, while natural language processing experiments obtain 93 % accuracy with 50 sets of learning data.
机译:人工智能技术发现人机互动一直在增长。人机相互作用的发展导致更自然的相互作用。在日常互动中,人类使用言语,比其他方式更占主导地位,例如手势和目光接触。言语是与语言系统密切相关的人类交流的发声形式。问题是含义,歧义,而不是根据语法规则的语言,导致命令转换变得更加复杂。要了解语音命令的含义,有必要了解句子的语义和句法结构。本研究将开发能够了解用于机器人应用的印度尼西亚语音命令的人工智能技术。本研究的目的是将语音命令转化为机器人操作,以产生更自然的人机交互。将使用Bark频率谱系数提取语音命令。使用神经网络将患者识别为单词。将使用自然语言处理处理完整句子中的单词,以便可以执行来自给定命令的含义和适当的操作。语音识别实验用28组语音信号获得82%的精度,而自然语言处理实验可以获得93%的精度,具有50套学习数据。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号