Optimized lossless audio compression using DCT energy thresholding and machine learning technique
DOI:
https://doi.org/10.7494/csci.2025.26.3.6427Abstract
In this paper, a novel lossless audio compression technique has been proposed, utilizing the Discrete Cosine Transform (DCT) coefficient-controlled technique based on energy thresholding, an XOR-based neural network compression model, and a CNN model. Initially, the DCT is applied to the input audio signal to achieve better energy compaction, followed by transforming selected DCT coefficients into a compressed binary stream. Subsequently, this binary stream is passed to two prediction-based optimized models: an XOR model and a CNN model for further compression. The binary stream is first processed by the neural network model for XOR operation, and the resulting output is then fed into a CNN model to reduce data dimensionality and generate compressed audio data. The simulation findings are analyzed using various statistical and robustness measures and compared with existing approaches.
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