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Fine-Tuning Audio Compression: Algorithmic Implementation and Performance Metrics

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  • Umer Ijaz

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

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.

Suggested Citation

  • Umer Ijaz, 2024. "Fine-Tuning Audio Compression: Algorithmic Implementation and Performance Metrics," International Journal of Innovations in Science & Technology, 50sea, vol. 6(1), pages 220-236, March.
    • Handle: RePEc:abq:ijist1:v:6:y:2024:i:1:p:220-236
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    File URL: https://journal.50sea.com/index.php/IJIST/article/view/714/1288
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