@inproceedings{basu2004mixing,
author = {Basu, Sumit},
title = {Mixing with Mozart},
year = {2004},
month = {November},
abstract = {A variety of tools exist in hardware and software for mixing dance music. These work by estimating the "beats-per-minute" count of music with heavy beats. These tools aid a DJ in finding the appropriate speed change and time shift to smoothly combine or transition between two pieces of music. In this work, we present a method for finding these alignments and combining a wider class of songs with dance music (e.g., Mozart with techno). We do this by jointly optimizing the energy alignment of both signals instead of attempting to detect individual beats/tempos. Though computationally intensive if naively computed, we introduce an approximation to greatly speed up the evaluation of the tens of thousands of possible matches. This results in a set of a few top choices for alignment parameters. We also develop a measure of the quality of the match to help assess whether the best alignment is actually a good fit. We show a variety of results demonstrating the use of this method.},
url = {http://approjects.co.za/?big=en-us/research/publication/mixing-with-mozart/},
}