Multichannel audio signal compression based on tensor decomposition

Abstract

This paper proposes a novel multichannel audio signal compression method based on tensor decomposition. The multichannel audio tensor space is established with three factors (channel, time, and frequency) and is decomposed into the core tensor and three factor matrices based on tucker model. Only the truncated core tensor is transmitted to the decoder which is multiplied by the factor matrices trained before processing. The performance of the proposed method is evaluated with approximation errors, compression degree and listening tests. When the core tensor is smaller, the compression degree will be higher. A very noticeable compression capability will be achieved with an acceptable retrieved quality. The novelty of the proposed method is that it enables both high compression capability and backward compatibility with little signal distortion to the hearing.