A new speech/non-speech classification method using minimal Walsh basis functions

In this paper, a method to distinguish between the closely located speech and non-speech segments of noisy speech signals is presented. It is based on modification of the original signal with the help of minimal binary Walsh basis functions and an analysis/synthesis scheme. Then, the presence of speech/non-speech segments is determined from the modified signals with a simple decision scheme. Besides its simplicity, the simulation results are promising and significantly better than G.729B with signal to noise ratio (SNR) as low as 0 dB in different noisy environments.