SPARSE DECOMPOSITION OF AUDIO SIGNALS USING A PERCEPTUAL MEASURE OF DISTORTION. APPLICATION TO LOSSY AUDIO CODING.

Ichrak Toumi (1) , Olivier Derrien (2, 1)

1 LMA - Laboratoire de Mécanique et d'Acoustique [Marseille]
2 UTLN - Université de Toulon

State-of the art audio codecs use time-frequency transforms derived from cosine bases, followed by a quantification stage. The quantization steps are set according to perceptual considerations. In the last decade, several studies applied adaptive sparse time-frequency transforms to audio coding, e.g. on unions of cosine bases using a Matching-Pursuit-derived algorithm. This was shown to significantly improve the coding efficiency. We propose another approach based on a variational algorithm, i.e. the optimization of a cost function taking into account both a perceptual distortion measure derived form a hearing model and a sparsity constraint, which favors the coding efficiency. In this early version, we show that, using a coding scheme without perceptual control of quantization, our method outperforms a codec from the literature with the same quantization scheme. In future work, a more sophisticated quantization scheme would probably allow our method to challenge standard codecs e.g. AAC.

Mots clés: Index Terms– Audio coding; Sparse approximation; Iterative thresholding algorithm; Perceptual model

Domaines: Traitement du signal et de l'image [eess.SP]

Ichrak Toumi, Olivier Derrien. SPARSE DECOMPOSITION OF AUDIO SIGNALS USING A PERCEPTUAL MEASURE OF DISTORTION. APPLICATION TO LOSSY AUDIO CODING.. 18th International Conference on Digital Audio Effects, Norwegian University of Science and Technology, Nov 2015, Trondheim, Norway. ⟨hal-01240863⟩