Audio Compression Using Graph-based Transform

TL;DR

This paper introduces a graph-based transform for audio compression that outperforms traditional methods like DCT and WHT in decorrelation efficiency, leveraging a novel graph structure for audio signals.

Contribution

The paper proposes a new graph-based transform tailored for audio compression, including a specific graph structure and eigenvector projection approach.

Findings

Outperforms DCT and WHT in decorrelation

Produces sparser coefficients for audio signals

Demonstrates improved compression potential

Abstract

Graph-based Transform is one of the recent transform coding methods which has been used successfully in the state-of-art data decorrelation applications. In this paper, we propose a Graph-based Transform (GT) for audio compression. Hence, we introduce a proper graph structure for audio. Then the audio frames are projected onto an orthogonal matrix consisting of eigenvectors of the introduced graph matrix, leading to the sparse coefficients. The results show that the proposed method outperforms the conventional transform methods like Discrete Cosine Transform (DCT) and Walsh-Hadamard Transform (WHT) in decorrelation of the audio signals.