The SongGen project consists of a complete automated data processing system with a three-phase workflow:
- Raw data processing: Automatic cleaning of invalid audio, harmonized sample rates and bit depths
- feature extraction: Parallel extraction of musical features such as Mel's spectrum, fundamental frequency, volume, etc.
- quality assurance: Data quality scoring via multi-model Ensemble
This pipeline processed dataset has:
- Standardized audio parameters (16kHz/16bit)
- Accurate time-aligned labeling of lyrics
- Rich music attribute tags
The open-source data processing code allows community contributors to extend support for new music datasets, and this open ecological design accelerates the iterative evolution of model capabilities.
This answer comes from the articleSongGen: A Single-Stage Autoregressive Transformer for Automatic Song GenerationThe
May not be reproduced without permission:AI productivity tools " SongGen's data processing pipeline ensures consistent quality of training data
