Fine-Tuning Audio Compression: Algorithmic Implementation and Performance Metrics

Umer Ijaz ()
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Umer Ijaz: Department of Electrical Engineering & Technology, Government College University, Faisalabad, Pakistan

International Journal of Innovations in Science & Technology, 2024, vol. 6, issue 1, 220-236

Abstract: Introduction/Importance of Study:This study introduces a comprehensive evaluation of audio compression algorithms to address the increasing demand for efficient data compression techniques in various audio processing applications.Novelty statement:Our research contributes novel insights into the comparative analysis of audio compression algorithms, offering a systematic approach to assess performance across multiple dimensions.Material and Method:The research methodology involved the selection of a diverse dataset comprising five audio files, rigorous implementation of four prominent compression algorithms, and systematic evaluation of performance metrics.Results and Discussion:The abstract primarily focuses on presenting the findings of the comparative analysis, highlighting the performance of MP3, LPC, Wavelet, and Sub band algorithms across various evaluation parameters.Concluding Remarks:In conclusion, our study identifies Wavelet compression as the optimal choice among the evaluated algorithms, offering exceptional accuracy, perceptual quality, and minimal distortion in audio compression.

Keywords: Audio Compression; Algorithm Evaluation; MP3 Compression; LPC Compression; Wavelet Compression; Subband Compression; Performance Metrics; Comparative Study; Digital Signal Processing; Multimedia Applications (search for similar items in EconPapers)
Date: 2024
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