Speech signal denoising based on GWO-VMD combined with MODWT

To minimize the impact of noise on speech signals during transmission or recording. In this paper, a denoising method for speech signals is introduced, which integrates GWO-VMD with MODWT. Firstly, the combination of VMD decomposition parameters (k, α) is optimized using the GWO algorithm. The optimized VMD is used to decompose the signal and the IMF component with lower correlation coefficient is eliminated according to the correlation coefficient screening principle. Secondly, the remaining IMFs are recombined and multi-scale analysis is performed by MODWT. Finally, the wavelet coefficients with relative energy greater than a certain threshold are reconstructed to derive the denoised signal. Experimental outcomes demonstrate that by using GWO-VMD-MODWT for noise reduction, the signal-to-noise ratio (SNR) of the original noisy speech signal has increased from -1.0416dB to 11.6057dB. The root mean square error (RMSE) has decreased from 0.0998 to 0.0233. The noise reduction capability of the integrated denoising method presented in this paper surpasses that of the single VMD and MODWT denoising method, as well as the classical EMD and EWT denoising method.