Automatic music transcription and audio source separation

被引:48
作者
Plumbley, MD [1 ]
Abdallah, SA [1 ]
Bello, JP [1 ]
Davies, ME [1 ]
Monti, G [1 ]
Sandler, MB [1 ]
机构
[1] Univ London Queen Mary Coll, Dept Elect Engn, London E1 4NS, England
基金
美国国家科学基金会;
关键词
D O I
10.1080/01969720290040777
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this article, we give an overview of a range of approaches to the analysis and separation of musical audio. In particular, we consider the problems of automatic music transcription and audio source separation, which are of particular interest to our group. Monophonic music transcription, where a single note is present at one time, can be tackled using an autocorrelation-based method. For polyphonic music transcription, with several notes at any time, other approaches can be used, such as a blackboard model or a multiple-cause/sparse coding method. The latter is based on ideas and methods related to independent component analysis (ICA), a method for sound source separation.
引用
收藏
页码:603 / 627
页数:25
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