Fine-Tuning Audio Compression: Algorithmic Implementation and Performance Metrics
Journal Title: International Journal of Innovations in Science and Technology - Year 2024, Vol 6, Issue 1
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.
Authors and Affiliations
Umer Ijaz, Fouzia Gillani, Ali Iqbal, Muhammad Saad Sharif, Muhammad Fraz Anwar, Abubaker Ijaz
Keywords
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