A bioinspired spectro-temporal domain for sound denoising

J. GODDARD; H. RUFINER; C. MARTÍNEZ; L. DI PERSIA; D. MILONE

Buenos Aires

Simposio; XVII Simposio Argentino de Inteligencia Artificial - 45 Jornadas Argentinas de Informática; 2016

Universidad de Tres de Febrero

The representation of sound signals at the cochlea and auditory cortical level has been studied as an alternative to classical analysis methods. In this work, we put forward a recently proposed feature extraction method called approximate auditory cortical representation, based on an approximation to the statistics of discharge patterns at the primary auditory cortex. The approach here proposed estimates a non-negative sparse coding with a combined dictionary of atoms calculated from clean signal and noise. The denoising is carried out on noisy signals by the reconstruction of the signal discarding the atoms corresponding to the noise. Results on synthetic and real data show that the proposed method improves the quality of the signals, mainly under severe degradation.