Application of Variational Mode Decomposition on Speech Enhancement
Rashmirekha Ram, Sabyasachi Patra, Mihir Narayan Mohanty
Citation: Proceedings of the Second International Conference on Research in Intelligent and Computing in Engineering, Vijender Kumar Solanki, Vijay Bhasker Semwal, Rubén González Crespo, Vishwanath Bijalwan (eds). ACSIS, Vol. 10, pages 293–296 (2017)
Abstract. Enhancement of speech signal and reduction of noise from speech is still a challenging task for researchers. Out of many methods signal decomposition method attracts a lot in recent years. Empirical Mode Decomposition (EMD) has been applied in many problems of decomposition. Recently Variational Mode Decomposition (VMD) is introduced as an alternative to it that can easily separate the signals of similar frequencies. This paper proposes the signal decomposition algorithm as VMD for denoising and enhancement of speech signal. VMD decomposes the recorded speech signal into several modes. Speech contaminated with different types of noise is adaptively decomposed into various components is said to be Intrinsic Mode Functions (IMFs) by shifting process as in Empirical Mode decomposition (EMD) method. Next to it the denoising technique is applied using VMD. Each of the decomposed modes is compact. The simulation result shows that the proposed method is well suited for the speech enhancement and removal of noise by restoring the original signal.
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