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Harmonic analysis using neural networks.

Tsui, Wan Shun Vincent.

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Harmonic analysis using neural networks.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Harmonic analysis using neural networks./
作者:	Tsui, Wan Shun Vincent.
面頁冊數:	96 p.
附註:	Adviser: W. James MacLean.
Contained By:	Masters Abstracts International41-03.
標題:	Artificial Intelligence. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MQ73966
ISBN:	061273966X

Harmonic analysis using neural networks.
Tsui, Wan Shun Vincent.

Harmonic analysis using neural networks. - 96 p.

Adviser: W. James MacLean.

Thesis (M.A.Sc.)--University of Toronto (Canada), 2002.

This thesis describes a system of neural networks that performs harmonic analysis on musical compositions. The system is split into four groups of Networks: Key Network, Root Network A (used to detect secondary functions), Root Network B, and Quality Network. The system is trained on 20 J. S. Bach chorales and tested on another 18 Bach chorales. Accuracies of over 90% were obtained for all four groups of Networks. Comparison with a modified version of Krumhansl's key-finding algorithm indicates Key Network outperforms it by more than 16% in overall accuracy. This work has potential for extension into music of other composers or genres. Also, this work can be used by a computer accompanist to determine the key of an improvising soloist.

ISBN: 061273966XSubjects--Topical Terms:

769149
Artificial Intelligence.

Harmonic analysis using neural networks.
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502 $a Thesis (M.A.Sc.)--University of Toronto (Canada), 2002.
520 $a This thesis describes a system of neural networks that performs harmonic analysis on musical compositions. The system is split into four groups of Networks: Key Network, Root Network A (used to detect secondary functions), Root Network B, and Quality Network. The system is trained on 20 J. S. Bach chorales and tested on another 18 Bach chorales. Accuracies of over 90% were obtained for all four groups of Networks. Comparison with a modified version of Krumhansl's key-finding algorithm indicates Key Network outperforms it by more than 16% in overall accuracy. This work has potential for extension into music of other composers or genres. Also, this work can be used by a computer accompanist to determine the key of an improvising soloist.
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