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Authors
Affiliations
1 Department of Information Technology, Technocrat Institute of Technology-Bhopal (M.P.), IN
2 Department of Information Technology,
Technocrat Institute of Technology-Bhopal (M.P.), IN
3 MATS University, Raipur (C.G.), IN
4 Multimedia Research Department, Multimedia
Regional Center, Madhya Pradesh Bhoj (Open) University, Khandwa Road Campus, Indore (M.P.), IN
5 Technocrats Institute of Technology, Bhopal (M.P.), IN
Source
Biometrics and Bioinformatics, Vol 2, No 2 (2010), Pagination: 1-12
Abstract
In this project report, (i.e. “Result Analysis to Compute Entropy of Voice Signal (CEVS) SNR using Matlab”) an approach is used to compute the entropy of given voice signal and signal to noise ratio (SNR) with the help of computed entropy. The main goals of this project are:
• To compute the tone of inputted voice signal
• To estimate entropy of tone
• To calculate SNR of entropy
To do this, psychoacoustic model and wavelet toolbox is used. Psychoacoustic model calculates masking threshold. Maximum distortion energy is computed from computed tone of inputted voice signal which defines the CEVS and SNR.
Keywords
Matlab 6.5, Wavelet Toolbox, Psychoacoustic Model, Algorithm.
