A Survey on Filtering Methods Used to Remove Noise in Speech and Music Signal

The most reliable way people around the world communicate, relax and enjoy is through speech and music signals. So, it is important to get these signals in their pure form. But in our living environment, getting a clear signal is challenging. Along with our required signal, sounds from other sources called noises are also mixed and degrade the original. Different filtering methods are used to remove noises from a signal. Filtering methods include different filters and autoencoders. Filters are designed in such a way that they will remove a particular type of noise. Denoising autoencoders are another option for noise removal. Autoencoders are a type of artificial neural network that encodes and decodes data in an unsupervised learning method and filters the noise. This paper examines noises in speech and music signals and different filtering methods to remove these noises. The filtering methods include filters and autoencoders. Different methods are investigated and suggested that the extended forms of filters or combination of filters or combining filters with autoencoder results in better noise removal than they are used individually.