Audio DB Converter

The Audio DB Converter processes large sets of audio metadata by translating a source schema into a target schema while preserving data integrity. It is designed for catalogers, librarians, and engineers who manage music, podcast, or sound archives across platforms. Conceptually, the tool loads source metadata, applies a user-defined field mapping, normalizes values (durations, dates, license fields), and outputs a migrated dataset that aligns with the destination schema. It supports batch processing and preserves provenance to track original values. The tool can emit outputs in CSV or JSON and can export to downstream systems when connected to a data pipeline. Unique value lies in schema-aware mapping that handles cross-version constructs (ID3 versus Vorbis comments, or MP4 metadata) and in-built validation to catch missing or incompatible fields before migration. It addresses typical use cases such as migrating from a legacy catalog to a standard metadata schema, consolidating fields from multiple sources, or preparing data for ingestion into a Digital Asset Management system. Core features include field-level mappings, data normalization (durations to seconds, dates to ISO 8601), cross-field validation, and optional multilingual field handling. The tool benefits music libraries, broadcasters, and archives that require consistent metadata across platforms and formats. Outputs support interoperability with data lakes, catalogs, and content management systems, enabling reliable searchability and asset discovery.