Proposing a New Method for Separating Speech from Background Music Based on Discrete Wavelet Coefficient and Self Organizing Map Neural Network

The problem of separating speech from background music is a fascinating but difficult and challenging problem for the lack of information about the original music and speech. In this article, we used the discrete wavelet transform for using the time-frequency information of the combined signal. In the proposed method after obtaining the energy of the decomposed wavelet coefficients, these coefficients are classified using SOM neural network. The experimental results, confirmed the capability of the proposed method in mean opinion score (MOS) and signal distortion ratio (SDR) results.