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Research on Cooperative Control of Human-Computer Interaction Tools with High Recognition Rate Based on Neural Network

机译:基于神经网络的高识别率的人机交互工具合作控制研究

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Human-Computer Interaction (HCI) is the vital technology of Virtual Reality. The control using several different HCI tools together provides a natural and effective method of human-computer interaction. This paper provides a way of cooperative control with multi-recognition tools. The separate tools, including speech recognition tools, hand gesture recognition tools, posture recognition tools, are developed firstly. Then assign the cooperation program receives the recognition result sent from the three independent tool through UDP protocol. A neural network that fits the habits of the operator is trained. Process the three recognition results using the trained BP neural network. Higher recognition rate compared with a single HCI tool is accomplished. Operators can communicate with the machine much more naturally and effectively.
机译:人机互动(HCI)是虚拟现实的重要技术。使用几种不同的HCI工具的控制共同提供了一种自然和有效的人机交互方法。本文提供了一种与多识别工具的合作控制方式。首先开发了单独的工具,包括语音识别工具,手势识别工具,姿势识别工具。然后分配合作程序通过UDP协议接收从三个独立工具发送的识别结果。培训符合操作员习惯的神经网络。使用培训的BP神经网络处理三个识别结果。完成与单个HCI工具相比的较高识别率。操作员可以更自然和有效地与机器通信。

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