MySong: automatic accompaniment generation for vocal melodies

Authors:
Ian Simon;Dan Morris;Sumit Basu
Affiliations:
University of Washington, Seattle, WA, USA;Microsoft Research, Redmond, WA, USA;Microsoft Research, Redmond, WA, USA
Venue:
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Year:
2008

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Abstract

We introduce MySong, a system that automatically chooses chords to accompany a vocal melody. A user with no musical experience can create a song with instrumental accompaniment just by singing into a microphone, and can experiment with different styles and chord patterns using interactions designed to be intuitive to non-musicians. We describe the implementation of MySong, which trains a Hidden Markov Model using a music database and uses that model to select chords for new melodies. Model parameters are intuitively exposed to the user. We present results from a study demonstrating that chords assigned to melodies using MySong and chords assigned manually by musicians receive similar subjective ratings. We then present results from a second study showing that thirteen users with no background in music theory are able to rapidly create musical accompaniments using MySong, and that these accompaniments are rated positively by evaluators.