A Fixed Dimension Modified Sinusoid Model (FD-MSM) for Single Microphone Sound Separation

The lack of a flexible analysis model has been introduced as an important issue in different applications like source separation. In this paper, a fixed dimension modified sinusoid model (FD-MSM) is proposed for analysis of all audible signals consisting of speech, music and their mixtures. Employing the peak picking in Meldomain gives rise to a fixed number of parameters in the proposed FDMSM, which is desired in clustering algorithms like VQ (vector quantization) or GMM (gaussian mixture model), commonly used for source separation scenarios. Applying the proposed FD-MSM to various audible signals, it is observed that the resulting signal is perceptually indistinguishable from the original.