This paper is published in Volume-3, Issue-4, 2017
Area
Speech Processing
Author
Nishitha Danthi, Dr. A. R Aswatha
Org/Univ
Dayananda Sagar College Of Engineering, Bengaluru, Karnataka, India
Keywords
Speech Enhancement, Windowing, VAD, MFCC, HMM.
Citations
IEEE
Nishitha Danthi, Dr. A. R Aswatha. Speech Recognition in Noisy Environment-an Implementation on MATLAB, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Nishitha Danthi, Dr. A. R Aswatha (2017). Speech Recognition in Noisy Environment-an Implementation on MATLAB. International Journal of Advance Research, Ideas and Innovations in Technology, 3(4) www.IJARIIT.com.
MLA
Nishitha Danthi, Dr. A. R Aswatha. "Speech Recognition in Noisy Environment-an Implementation on MATLAB." International Journal of Advance Research, Ideas and Innovations in Technology 3.4 (2017). www.IJARIIT.com.
Nishitha Danthi, Dr. A. R Aswatha. Speech Recognition in Noisy Environment-an Implementation on MATLAB, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Nishitha Danthi, Dr. A. R Aswatha (2017). Speech Recognition in Noisy Environment-an Implementation on MATLAB. International Journal of Advance Research, Ideas and Innovations in Technology, 3(4) www.IJARIIT.com.
MLA
Nishitha Danthi, Dr. A. R Aswatha. "Speech Recognition in Noisy Environment-an Implementation on MATLAB." International Journal of Advance Research, Ideas and Innovations in Technology 3.4 (2017). www.IJARIIT.com.
Abstract
Speech is one of the ways to express ourselves naturally. So, speech can be used as a means to communicate with machines. In this work, using MATLAB as a platform isolated word recognizer is achieved. Speech signals get distorted by many kinds of noises. Hence, it is necessary to reduce the noise contained in the speech signal. This is called speech enhancement. Speech enhancement aims at improving the intelligibility of the speech. Noise has been removed using Spectral Subtraction with Over Subtraction technique. The feature extraction is carried out using MFCC and feature matching is achieved using HMM.