Bioinformatický seminár

Mon 1 Mar. 2010, 14:00
C

Title: From DNA to Jay-Z: how ideas from bioinformatics can automate finding rhymes in rap music
Speaker: Daniel G. Brown, University of Waterloo, Canada

Abstract:
Unlike most kinds of music, the core of rap music is found in the
rhythm and rhyme of its lyrics.  Different artists or subgenres
will use different kinds of rhyme, which in some cases can be
extremely complicated: the end of one line may rhyme with several
parts of the previous line, and in some cases, rhymes may be
imperfect.

Detecting these complex rhyme patterns manually is time consuming
and tedious.  We have designed a system for automatic rhyme
annotation. Our approach is founded on several bioinformatics
ideas.  First, using a test corpus of known rhymes, we develop a
probabilistic model of rhymed and unrhymed syllables.  Then, we
use that model to build a log-likelihood ratio scoring matrix for
identifying what is and is not a rhyme.  Finally, we create a
local alignment procedure to find high-scoring lyrics segments.

Our procedure has high sensitivity and specificity in identifying
true rhymes in an annotated corpus; essentially, it identifies
most complex rhymes, and identifies few false rhymes.  We can use
it to characterize artists, and then to develop classifiers for
individual artists with surprising success.

Joint work with MMath student Hussein Hirjee

Bio:
Dan Brown is Associate Professor of Computer Science at the
University of Waterloo, where he has been since 2001.  From 2000
to 2001, he worked on the human and mouse genome projects at the
Whitehead/MIT Center for Genome Research.  His interests are in
algorithms for understanding the information in discrete
sequences, particularly identifying patterns in DNA and protein
sequences.