Wavelet Decompositions, Hierarchical Encoding and Convolutional Neural Network Integrated Lossless Audio Codec
Abstract
In this paper, a lossless audio codec is proposed by leveraging Wavelet transformation, Hierarchical encoding with Convolutional Neural Network architecture. In the first phase, three level 1D wavelet decomposition is applied on the input audio for generating approximation and detail coefficients. In the next phase, the approximation and detail coefficients are transformed into binary streams by utilizing the proposed dynamic hierarchical encoding algorithm. In this encoding technique, coefficients are converted to binary by dynamically accumulating the binary path values. In the subsequent phase, the binary stream is transformed into image patterns and further compressed by reducing the dimensionality by the proposed convolutional neural network(CNN) model. The model’s effectiveness is evaluated against current conventional lossless audio benchmarks and machine learning-based methods. Experiment results demonstrate that the method shows better performance than existing lossless audio techniques.References
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