Audio Compression Using Graph-based Transform
This work addresses audio compression for signal processing applications, but it appears incremental as it adapts an existing graph-based method to audio.
The authors tackled audio compression by proposing a Graph-based Transform (GT) that projects audio frames onto eigenvectors of a graph matrix to achieve sparser coefficients, resulting in better decorrelation performance compared to conventional methods like DCT and WHT.
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.