Speech enhancement by end point detection and signal subspace method

In this paper end point detection, MFCC and signal subspace Algorithm is proposed for speech enhancement. end point detection, MFCC and signal subspace Algorithm is used to reduce external noise, improve the quality of signal, and reduce signal loss. The main problem in speech communication is the background noise. It is not useful to keep the communication if the noise of the subway, train, car, etc., prevents us from understanding. The earliest and most commonly used method of speech enhancement is magnitude spectral subtraction. The result table shows fair improvements in peak SNR in the speech signal. We have tested this algorithm on different frequency signals and with different levels of noise in the signal. At each level, the PSNR is in improved as compared to the noisy signal. This shows that the noise is removed to a great extent from the noisy speech signal.