Assessment of musical noise using localization of isolated peaks in time-frequency domain

Abstract : Musical noise is a recurrent issue that appears in spectral techniques for denoising or blind source separation. Due to localised errors of estimation, isolated peaks may appear in the processed spectrograms, resulting in annoying tonal sounds after synthesis known as "musical noise". In this paper, we propose a method to assess the amount of musical noise in an audio signal, by characterising the impact of these artificial isolated peaks on the processed sound. It turns out that because of the constraints between STFT coefficients, the isolated peaks are described as time-frequency "spots" in the spectrogram of the processed audio signal. The quantification of these "spots" , achieved through the adaptation of a method for localisation of significant STFT regions, allows for an evaluation of the amount of musical noise. We believe that this will pave the way to an objective measure and a better understanding of this phenomenon.
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Ronan Hamon, Valentin Emiya, Lucas Rencker, Wenwu Wang, Mark Plumbley. Assessment of musical noise using localization of isolated peaks in time-frequency domain. The 42nd IEEE International Conference on Acoustics, Speech and Signal Processing, Mar 2017, New Orleans, United States. ⟨hal-01472614⟩

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