The Restoration of Single Channel Audio Recordings Based on Non-Negative Matrix Factorization and Perceptual Suppression Rule
In this paper, we focus on the signal-to-noise ratio (SNR) improvement in single channel audio recordings. Many approaches have been reported in the literature. The most popular method, with many variants, is Short Time Spectral Attenuation (STSA). Although this method reduces the noise and improves the SNR, it mostly tends to introduce signal distortion and a perceptually annoying residual noise usually called musical noise. In this paper we investigate the use of Non-negative Matrix Factorization (NMF) as an alternative to the STSA for the digital curation of musical heritage. NMF is an emerging new technique in the blind extraction of signals recorded in a variety of different fields. The application of NMF to the analysis of monaural recordings is relatively recent. We show that NMF is a suitable technique to extract the clean audio signal from undesired non stationary noise in a monaural recording of ethnic music. More specifically, we introduce a perceptual suppression rule to determine how the perceptual domain is competitive compared to the acoustic domain. Moreover, we carry out a listening test in order to compare NMF with the state of the art audio restoration framework using the EBU MUSHRA test method. The encouraging results obtained with this methodology in the presented case study support their wider applicability in audio separation.