Effects of Soft-Masking Function on Spectrogram-Based Instrument - Vocal Separation
Authors: Duc Chung Tran; M.K.A. Ahamed Khan
Abstract: This paper presents an analysis of effects of soft-masking function on spectrogram-based instrument - vocal separation for audio signals. The function taken into consideration is of 1st-order with two masking magnitude parameters: one for background and one foreground separation. It is found that as the masking magnitude increases, the signal estimations are improved. The background signal’s spectrogram becomes closer to that of the original signal while the foreground signal’s spectrogram represents better the vocal wiggle lines compared to the original signal spectrogram. With the same increase in the masking magnitude (up to ten-fold), the effect on background signal spectrogram is more significant compared to that of foreground signal. This is evident through the significant (≈≈three times) reduction of background signal’s root-mean-square (RMS) values and the less significant reduction (approximately one-third) of foreground signal’s RMS values.
Published: 02 July 2020