论文标题
基于HMM的音素语音识别系统，用于控制和命令工业机器人
HMM-based phoneme speech recognition system for control and command of industrial robots
论文作者
论文摘要
语音识别是一项杰出的技术，它可以通过人类机器人互动（HRI）来帮助我们通过语音开发自然语言界面。它允许计算机采用口语说明，解释并从中生成文本。在本文中，我们提出了一个基于音素的语音识别系统来控制工业机器人。在减少机器人操作员控制和指挥机器人的努力方面，语音识别已成为流行的界面之一。本文旨在研究线性预测编码技术的潜力，以开发用于机器人技术应用的稳定且强大的音素语音识别系统。我们的系统分为三个段：麦克风阵列，一个语音模块和一个3多型机器人臂。为了验证我们的方法，我们已经使用简单而复杂的句子进行了测试，以用于各种机器人活动，例如操纵立方体并选择和放置任务。此外，我们还分析了测试结果，以纠正我们方法中的问题和局限性。本文介绍了我们通过对项目进行实验实现的所有测试结果。
Speech recognition is a prominent technology, which helps us to develop a Natural language interface through speech for the Human-Robot Interaction (HRI). It allows the computer to take the spoken instructions, interpret it, and generate text from it. In this paper, we propose a phoneme based speech recognition system to control industrial robots. Speech recognition has become one of the popular interfaces when it comes to reducing robot operator's efforts to control and command the robot. This paper intends to investigate the potential of Linear Predictive coding technique to develop a stable and robust phoneme speech recognition system for robotics applications. Our system is divided into three segments: a microphone array, a voice module, and a 3-DOF robotic arm. To validate our approach, we have performed tests with simple and complex sentences for various robotics activities like manipulating a cube and pick and place tasks. Moreover, we also analyzed the test result to rectify the problems and limitations in our approach. The paper presents all the test results which we have achieved through conducting experiments on our project.
