Audio Analyzer

Audio Analyzer provides programmable audio metrics via a Node.js library, enabling automated validation and feature extraction for large collections. It decodes common formats, reads metadata, and returns core timing and spectral data for pipelines and catalogs. Conceptually, the tool decodes the file, measures duration and sample characteristics, and then runs signal processing to derive frequency-domain features and loudness estimates. This combination supports quality control, metadata enrichment, and analytics for music, podcasts, and sound libraries. Beneficiaries include media platforms, content producers, and QA teams seeking repeatable measurements that scale across thousands of assets. Unique value lies in its scriptable, library-first approach with a rich metric set, compatibility with both CommonJS and ESM, and output suitable for CI and data lakes. Core features include file-based decoding, duration, sample rate, channels, bits per sample, and optional LUFS-like loudness, spectral centroid, bandwidth, tempo, and silence detection. Use cases span automated cataloging, quality assurance, and feature engineering for recommendation or search systems. The tool outputs a structured JSON metrics object, enabling easy integration into existing pipelines and analytics dashboards. This design favors accuracy, consistency, and scalability in asset-heavy environments, supporting large-scale processing with minimal manual intervention.