Analysis of words: algorithms for biological sequences, music and texts

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We will develop new methods in three interrelated areas of computer science: bioinformatics, music information retrieval and computational creativity. All three projects will develop the skills of young Canadian researchers to work in the new economy.******For bioinformatics, our focus is on building better methods for reconstructing evolutionary trees. We have previously designed extremely fast algorithms for this problem that depend on sequences being pre-aligned, and that depend on the high quality of those alignments. In this project, we will focus on the faster, but traditionally less accurate, methods that don't start with alignments, and build a hybrid system that merges some alignment approaches with existing alignment-free methods, to join high speed and high accuracy in this important evolutionary biology task.******In music information retrieval, our focus is on using bioinformatics algorithms to enhance similarity search in symbolically-represented music. We will develop methods that look for similar motifs and common patterns, as a way of identifying musical influence and historical changes in style. Our approach, derived from DNA sequence alignment, allows us to speed up what has traditionally been a slow area of music information retrieval; we may also be able to develop algorithms that work on recorded music.******Another focus is on music lyrics, where we will continue our work on analysis of patterns: rhyme, meter, wordplay, authorial voice, and other features. Previously, we have mostly focused on rap music, but we will also see to what extent we can characterize what makes a successful lyric in other genres, such as pop music. Preliminary work has suggested that highly complex rhymes predict song success and popularity on music sites like Shazam, and we will continue to explore the power and quality of lyrics.******Finally, in computational creativity, we will build a cyborg poet that combines current event news tweets with structure and style rules of successful poetry to build a "deadline poet" that responds to the news. We will investigate which features of tweets make them more and less successful in such a poet, and also analyze which other features are necessary to separate successful poems from unsuccessful ones. Along the way, we will also critique what it means to create artistic, creative objects from human-generated ones, and what this dichotomy has to say about whether computers can be creative agents.