Continuous Speech and Time-Frequency Transform Using the Kalman Filter

Authors

  • Mario Barnard Department of Electrical and Computer Engineering Oakland University Rochester, MI, USA
  • Mohamed Zohdy Department of Electrical and Computer Engineering Oakland University Rochester, MI, USA

DOI:

https://doi.org/10.24203/ijcit.v9i2.6

Keywords:

Kalman Filter, Radial Basis Function, Speech Recognition, Time-Frequency Transform, Continuous Speech

Abstract

In this paper, a Radial Basis Function-based Kalman filter has been utilized to in order to extended to the time-frequency transform, also called a spectrogram or spectrograph, and also been applied to simple continuous speech.

Downloads

Published

2020-03-15

Issue

Vol. 9 No. 2 (2020): March 2020

Section

Articles

License

Creative Commons License

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

The articles published in International Journal of Computer and Information Technology (IJCIT) is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

How to Cite

Continuous Speech and Time-Frequency Transform Using the Kalman Filter. (2020). International Journal of Computer and Information Technology(2279-0764), 9(2). https://doi.org/10.24203/ijcit.v9i2.6

Similar Articles

31-36 of 36

You may also start an advanced similarity search for this article.