Effect of feature normalization objective improvement of over Noisy Single-channel Speech Enhancement with Neural Networks
The signal obtained from the real world environment is often corrupted by means of unwanted noise. So, it is important to effectively ensure speech quality and obtain a noiseless speech signal of higher quality by applying the optimal noise cancellation technique. The main aim is to improve the speech intelligibility and speech quality. The signal obtained from the real world environment is often corrupted by means of unwanted noise. So, it is important to effectively ensure speech quality and obtain a noiseless speech signal of higher quality.se cancellation technique. Single Channel Speech Enhancement aims to reduce noise and retain speech quality to the best extent possible from noisy speech. Our overall assumption is that our noisy speech comes from addition of a clean speech and the noise signal and there is no other assumed distortion non-linear distortion, channel distortion and reverberation. The other general assumption we make is the noise attributes typically change slower than speech .to suppress noise, to retain speech to the best extent possible, to improving perception. In this Research work, our goal is for the end-users, the human listeners who are going to listen to the enhanced clips. So that will be our research investigated speech quality performances with help of neural networks.