1. bookVolume 118 (2021): Issue 1 (January 2021)
Journal Details
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Journal
First Published
20 May 2020
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1 time per year
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English
access type Open Access

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

Published Online: 05 Feb 2021
Page range: -
Received: 01 Jun 2020
Accepted: 05 Feb 2021
Journal Details
License
Format
Journal
First Published
20 May 2020
Publication timeframe
1 time per year
Languages
English
Abstract

In recent years, the integration of human-robot interaction with speech recognition has gained a lot of pace in the manufacturing industries. Conventional methods to control the robots include semi-autonomous, fully-autonomous, and wired methods. Operating through a teaching pendant or a joystick is easy to implement but is not effective when the robot is deployed to perform complex repetitive tasks. Speech and touch are natural ways of communicating for humans and speech recognition, being the best option, is a 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 investigates the potential of the linear predictive coding technique to develop a stable and robust HMM-based phoneme speech recognition system for applications in robotics. Our system is divided into three segments: a microphone array, a voice module, and a robotic arm with three degrees of freedom (DOF). To validate our approach, we performed experiments with simple and complex sentences for various robotic activities such as manipulating a cube and pick and place tasks. Moreover, we also analyzed the test results to rectify problems including accuracy and recognition score.

Keywords

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