CITATION — REFERENCE ENTRY
MySong: Automatic accompaniment generation for vocal melodies — Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2008)
- Key
- simon2008-mysong
- Authors
- Simon, Ian; Morris, Dan; Basu, Sumit
- Issued
- 2008
- Type
- paper-conference
- Container
- Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2008)
- Pages
- 725-734
Raw CSL JSON
{
"DOI": "10.1145/1357054.1357169",
"URL": "https://www.microsoft.com/en-us/research/uploads/prod/2016/02/mysongchi2008.pdf",
"page": "725-734",
"type": "paper-conference",
"title": "MySong: Automatic accompaniment generation for vocal melodies",
"author": [
{
"given": "Ian",
"family": "Simon"
},
{
"given": "Dan",
"family": "Morris"
},
{
"given": "Sumit",
"family": "Basu"
}
],
"issued": {
"date-parts": [
[
2008
]
]
},
"event-place": "Florence, Italy",
"container-title": "Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2008)"
}
Claims
-
MySong automatically chooses chords to accompany a vocal melody sung into a microphone, using a hidden Markov model trained on a music database. In a study, accompaniments made with MySong received subjective ratings similar to chords assigned manually by musicians.
"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 [...]. 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. [...] We present results from a study demonstrating that chords assigned to melodies using MySong and chords assigned manually by musicians receive similar subjective ratings."
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