Phonotopic Optimization: A Bio-Inspired Framework for Audio Data Compression Using Cortical Map Principles
Posted: Feb 28, 2024
Abstract
This paper introduces Phonotopic Optimization, a novel bio-inspired data compression framework that mimics the tonotopic organization of the auditory cortex. Unlike traditional compression algorithms that rely on statistical redundancy or perceptual models, our approach organizes audio data according to frequency-specific spatial mappings observed in mammalian auditory processing. We developed a computational model that transforms audio signals into a phonotopic representation, enabling efficient encoding through cortical-inspired sparse coding. Experimental results demonstrate a 27% improvement in compression ratios for musical audio while maintaining superior psychoacoustic fidelity compared to MP3 and AAC standards. The framework also exhibits emergent properties including graceful degradation and content-adaptive compression, suggesting new directions for biologically-plausible signal processing.
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