🤖 AI Summary
Historic worship spaces face irreversible loss of acoustic characteristics due to renovation, disaster, or aging. Method: This study proposes a multi-scale acoustic preservation and audible reconstruction framework integrating architectural archaeology, impulse response inversion modeling, geometric acoustic simulation, machine learning–driven reverberation parameter inversion, HRTF-based personalized binaural rendering, and VR/AR immersive presentation, supported by a real-time audible evaluation system. Contributions/Results: It establishes—first for worship spaces—a systematic paradigm for acoustic digital archiving; introduces a standardized audible validation protocol; synthesizes over 120 key scholarly references; and implements acoustic documentation and public education initiatives across five endangered heritage sites, thereby advancing the scientific conservation and living transmission of cultural heritage’s auditory dimension.
