Speech-Based Vehicle Movement Control Solution

Authors

  • Gurpreet Kaur
  • Mohit Srivastava
  • Amod Kumar

DOI:

https://doi.org/10.26636/jtit.2021.149820

Keywords:

deep belief networks, mel frequency cepstral coefficient, speech recognition

Abstract

The article describes a speech-based robotic prototype designed to aid the movement of elderly or handicapped individuals. Mel frequency cepstral coefficients (MFCC) are used for the extraction of speech features and a deep belief network (DBN) is trained for the recognition of commands. The prototype was tested in a real-world environment and achieved an accuracy rate of 87.4%

Downloads

Download data is not yet available.

Downloads

Published

2021-09-30

Issue

No. 3 (2021)

Section

ARTICLES FROM THIS ISSUE

License

Copyright (c) 2021 Journal of Telecommunications and Information Technology

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
G. Kaur, M. Srivastava, and A. Kumar, “Speech-Based Vehicle Movement Control Solution”, JTIT, vol. 85, no. 3, pp. 72–77, Sep. 2021, doi: 10.26636/jtit.2021.149820.