HMM-based phoneme speech recognition system for control and command of
industrial robots
Abstract
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.