R

reproducible-research

Reproducible Python pipeline for the IEEE Access paper "A Seven-Year Higher-Order Ambisonics Recording Corpus" - corpus-wide figures (geography, timeline, room acoustics, loudness, session inventory), LaTeX-macro generation for every numeric claim, and the peer-review bootstrap uncertainty analysis for the microphone-comparison results.

Reproducible Python pipeline for the AES 160 Convention paper "Zylia ZM-1 vs. Harpex Spcmic: A Case Study of Higher-Order Ambisonic Recording Performance" (Express Paper #51, Copenhagen 2026). Reads B-format WAV files, computes spectral, loudness, spatial-energy, and directional metrics, and emits LaTeX \newcommand macros for the manuscript.