An Improved Multi-band Spectral Subtraction using Mel-scale
Ruibin Zhang, Jingen Liu · Procedia Computer Science · 2018
In order to improve the intelligibility and quality of speech signal under different noise environments, an improved multi-band spectral subtraction algorithm using Mel-scale is proposed in this paper. In this algorithm, the whole speech spectrum is divided into N subbands without overlapping each other using the Mel frequency domain, and uses spectral subtraction to obtain the estimated pure speech independently in each subband. By using various types of noise at various SNRs, the experimental data, including SNR, PESQ measure and non-professional hearing test, are obtained. The result show that the algorithm is superior to the multi-band spectral subtraction with uniform segmentation and the traditional spectral subtraction algorithm, without causing considerable signal distortion and remnant musical noise.