Publication Type:

Journal Article


Advances in Intelligent Systems and Computing, Springer, Volume 425, p.309-321 (2016)





Alternating direction method of multipliers, Data-adaptive method, Gaussian noise (electronic), Intrinsic Mode functions, Mode decomposition, Noisy speech signals, Objective quality measures, Signal processing, Speech, Speech communication, Speech enhancement, Speech signals, Wavelet shrinkage


This paper proposes a Variational Mode Decomposition (VMD) based approach for enhancement of speech signals distorted by white Gaussian noise.VMD is a data adaptive method which decomposes the signal into intrinsic mode functions (IMFs) by using the Alternating Direction Method of Multipliers (ADMM). Each IMF or mode will contain a center frequency and its harmonics. This paper tries to exploreVMDas a Speech enhancement technique. In the proposed method, the noisy speech signal is decomposed into IMFs using VMD. The noisy IMFs are enhanced using two methods; VMD based wavelet shrinkage (VMD-WS) and VMD based MMSE log STSA (VMD-MMSE). The speech signal distorted with different noise levels are enhanced using the VMD based methods. The level of noise reduction and speech signal quality are measured using the objective quality measures. © Springer International Publishing Switzerland 2016.

Cite this Research Publication

B. G. Gowri, Kumar, S. S., Mohan, N., and Soman, K. P., “A VMD based approach for speech enhancement”, Advances in Intelligent Systems and Computing, vol. 425, pp. 309-321, 2016.