AutoMashup: Automatic Music Mashups Creation

TL;DR

AutoMashup is a system that automates music mashup creation by leveraging source separation, music analysis, and compatibility estimation, revealing limitations of current audio embeddings in capturing perceptual coherence.

Contribution

The paper introduces AutoMashup and evaluates the effectiveness of pretrained audio models for compatibility estimation in mashup creation, highlighting their limitations.

Findings

Mashup compatibility is asymmetric based on track roles.

Current embeddings do not match perceptual coherence measured by COCOLA.

Limitations of general-purpose audio representations are identified.

Abstract

We introduce AutoMashup, a system for automatic mashup creation based on source separation, music analysis, and compatibility estimation. We propose using COCOLA to assess compatibility between separated stems and investigate whether general-purpose pretrained audio models (CLAP and MERT) can support zero-shot estimation of track pair compatibility. Our results show that mashup compatibility is asymmetric -- it depends on the role assigned to each track (vocals or accompaniment) -- and that current embeddings fail to reproduce the perceptual coherence measured by COCOLA. These findings underline the limitations of general-purpose audio representations for compatibility estimation in mashup creation.