Journal of Shanghai University(Natural Science Edition) ›› 2017, Vol. 23 ›› Issue (3): 333-341.doi: 10.12066/j.issn.1007-2861.1940

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Reduction of background audio noise for historical films based on non-negative matrix factorization

ZHANG Yejun, YANG Weiying   

  1. Shanghai Film Academy, Shanghai University, Shanghai 200072, China
  • Received:2017-05-02 Online:2017-06-30 Published:2017-06-30

Abstract:

Audio materials of numerous historical films suffer from low sound quality, noise and other problems after being archived for a long time. This paper proposes a method based on non-negative matrix factorization (NMF) to automatically detect and separate background noise in a single channel audio. Harmonic signals and noises are modeled and differentiated using a sinusoid model and a priori noise training model respectively. Background noise is separated from the input audio with a constrained NMF algorithm. Experiments show that the proposed denoising algorithm outperforms the current algorithms in the denoise plug-in.

Key words: audio denoising, blind source separation, noise model training, non-negative matrix factorization