Cosmodoit: A Python Package for Adaptive, Efficient Pipelining of Feature Extraction from Performed Music
Integrates alignment, symbolic, and audio extraction in one modular pipeline.
Deep Dive
Cosmodoit, a Python package by Corentin Guichaoua, Daniel Bedoya, and Elaine Chew, integrates performance-to-score alignment with symbolic and audio feature extraction in a modular, flexible pipeline. It supports selective processing, dependency-aware computation, and incremental updates, reducing duplicated work and errors while enabling efficient large-scale processing across algorithms implemented in multiple languages.
Key Points
- Integrates performance-to-score alignment, symbolic extraction, and audio extraction in one pipeline
- Supports selective processing, dependency-aware computation, and incremental updates across languages
- Reduces duplicated work and errors while enabling efficient large-scale music performance analysis
Why It Matters
Unifies fragmented tools into one Python package, making large-scale music analysis faster and more reliable.