Abstract
Compared with channel-based audio coding, the object-based audio coding has a definite advantage in meeting the user’s demands of personalized control. However, in the conventional Spatial Audio Object Coding (SAOC), each frame is divided into 28 sub-bands. All frequency points in one sub-band share the common parameter. Under the SAOC framework, the bitrate can be saved, but aliasing distortion is prone to occur, which will influence the listening experience of audiences. In order to obtain higher perceptual quality, we propose a Stacked Sparse Autoencoder (SSAE) pipeline as overlapped modules. Each module extracted the efficient feature of side information from its preceding module. Then we can reduce the dimensionality of side information parameters for saving bitrate, and well reconstruct audio objects, thereby providing favorable auditory perception. Compared with conventional SAOC, TS-SAOC, and SVD-SAOC, both objective and subjective results show that the proposed method can achieve the best sound quality of the output signal at the same bitrate.
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Acknowledgment
This work was supported by the National Key R&D Program of China (No. 2017YFB1002803) and the National Nature Science Foundation of China (No. 61701194, No. U1736206).
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Wu, Y., Hu, R., Wang, X., Hu, C., Li, G. (2021). Stacked Sparse Autoencoder for Audio Object Coding. In: Lokoč, J., et al. MultiMedia Modeling. MMM 2021. Lecture Notes in Computer Science(), vol 12572. Springer, Cham. https://doi.org/10.1007/978-3-030-67832-6_5
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