In recent years integration of Human-Robot interaction with speech recognition has gained a lot of pace in the manufacturing industries. Undoubtedly, this bridges the large gap created between the operator and robot by communication’s point of view. Although there are numerous ways in which communication can be established between a human operator and the robot-like, controlling with a teaching pendant, or a joystick. Currently, the robots are controlled semi-autonomously by means of a computer. However, speech and touch [16] are natural ways of communication in humans, where speech recognition, being the best, is heavily researched technology. In this study, we aim at developing a stable and robust speech recognition system to allow humans to communicate with machines (Robotic-arm) in a seamless manner. This paper intends to investigate the potential of the Linear Predictive coding technique to develop a stable and robust HMM-based 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 (Figure 1). 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 results to rectify problems like accuracy, recognition score, etc. Also the paper briefly enumerates the future prospects and applications of our approach.

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.