An initial real-time speech enhancement method is presented to reduce the effects of additive noise. The method operates in the frequency domain and is a form of spectral subtraction. Initially, minimum statistics are used to generate an estimate of the noise signal in the frequency domain. The use of minimum statistics avoids the need for a voice activity detector (VAD) which has proven to be challenging to create. As minimum statistics are used, the noise signal estimate must be multiplied by a scaling factor before subtraction from the noise corrupted speech signal can take place. A spectral floor is applied to the difference to suppress the effects of "musical noise". Finally, a series of further enhancements are considered to reduce the effects of residual noise even further. These methods are compared using time-frequency plots to create the final speech enhancement design
@article{arxiv.2302.10313,
title = {Real-Time Speech Enhancement Using Spectral Subtraction with Minimum Statistics and Spectral Floor},
author = {Georgios Ioannides and Vasilios Rallis},
journal= {arXiv preprint arXiv:2302.10313},
year = {2023}
}