Very Low Bitrate Spatial Audio Coding with Dimensionality Reduction

Christian Rohlfing, Antoine Liutkus, Jeremy E.Cohen

Presented at the 42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017), 5-9 March 2017, New Orleans, USA
Conference homepage


In this paper, we show that tensor compression techniques based on randomization and partial observations are very useful for spatial audio object coding. In this application, we aim at transmitting several audio signals called objects from a coder to a decoder. A common strategy is to transmit only the downmix of the objects along some small information permitting reconstruction at the decoder. In practice, this is done by transmitting compressed versions of the objects spectrograms and separating the mix with Wiener filters. Previous research used nonnegative tensor factorizations in this context, with bitrates as low as 1 kbps per object.

Building on recent advances on tensor compression, we show that the computation time for encoding can be extremely reduced. Then, we demonstrate how the mixture can be exploited at the decoder to avoid the transmission of many parameters, permitting bitrates as low as 0.1 kbps per object for comparable performance.





NOTICE FOR IEEE PUBLICATIONS: © IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works, must be obtained from the IEEE. Contact: Manager, Copyrights and Permissions / IEEE Service Center / 445 Hoes Lane / P.O. Box 1331 / Piscataway, NJ 08855-1331, USA. Telephone: + Intl. 908-562-3966.