Environmental Noise Classification and Cancellation using Fuzzy Classifier and Fuzzy Adaptive Filters

The background noise is one of the major factors, which adversely affects the perceived grade of service in audio communication systems. The main problem in most of the environmental noise reduction system is source of noise signal which is to be used as a reference signal. Once the noise source is known then the noise elimination process will become easier. In any environmental conditions, predominant noise signal which is corrupting the original speech signal can be identified using neural network classification. In conventional gradient-based learning algorithms, tuning methods need to be differentiable and it leads to slow in convergence and if the noise is nonlinear, it will not provide a good generalization performance. To overcome this, an automatic noise reduction system is proposed which is an integration of fuzzy classifier and fuzzy adaptive filter.