An Automated Pop Song Mashup System

The Hong Kong University of Science and Technology
Department of Computer Science and Engineering


PhD Thesis Defence


Title: "An Automated Pop Song Mashup System"

By

Mr. Xinyang WU


Abstract:

Music mashups transform familiar recordings into new works by recombining 
elements of existing songs. The practice demands precise rhythmic alignment, 
musically compatible material, and a polished final mix. Automated systems 
have sought to replicate this craft, but they typically treat mashup creation 
as a single monolithic problem. Timing is aligned only globally, so small 
tempo errors accumulate over the course of a song. Compatibility between songs 
is judged by fixed similarity rules or binary classifiers that do not reflect 
the graded nature of listener preference. The final mixing stage receives the 
least attention of all, although stems from different productions must be made 
to sound as one.

This thesis argues that automated mashup generation becomes tractable when the 
problem is decomposed into three stages and when quality is measured as graded 
listener preference rather than a binary label. For temporal alignment, the 
system locates the rhythmic backbone of each song and corrects timing at the 
level of individual downbeats, so that the combined material stays locked to a 
shared beat. For musical compatibility, large-scale listening tests establish 
which combinations of separated stems listeners prefer, and a family of 
vocal-conditioned models learns the correspondence between vocals and 
accompaniment. For mix engineering, a restoration model corrects the tone and 
level of the instrumental so that it sits naturally beneath the vocal.

Together, these contributions form a modular, interpretable pipeline that 
edits and recombines real recordings rather than synthesizing new audio, 
preserving the identity that defines a mashup and keeping the result enjoyable 
to listen to.


Date:                   Tuesday, 25 August 2026

Time:                   1:00pm - 3:00pm

Venue:                  Room 2132A
                        Lift 22

Chairman:               

Committee Members:      Prof. Andrew HORNER (Supervisor)
                        Dr. Arpit NARECHANIA
                        Prof. Gary CHAN
                        Prof. Ross MURCH (ECE)
                        Dr. Jiafeng LIU (Central Conservatory)