DocumentCode :
3408855
Title :
Automatic Transcription Method for Polyphonic Music Based on Adaptive Comb Filter and Neural Network
Author :
Guibin, Zheng ; Sheng, Liu
Author_Institution :
Univ. of Harbin Eng., Harbin
fYear :
2007
fDate :
5-8 Aug. 2007
Firstpage :
2592
Lastpage :
2597
Abstract :
This paper presents a method to transcribe polyphonic music based on adaptive comb filter and neural network. In the method, the input audio is firstly divided into snapshots by a BP neural network, and then comb filters of different notes are used to calculate features. Comb filter can be adjusted to take inharmonicity and note pitch error into consideration. Note energy, audible harmonic number and harmonic continuity obtained from filter are used in BP neural network to recognize notes in snapshot, which helps multipitch estimation algorithm to be more robust to frequency missing and sharing.
Keywords :
adaptive filters; backpropagation; comb filters; electronic music; music; neural nets; adaptive comb filter; audible harmonic number; automatic transcription method; harmonic continuity; multipitch estimation algorithm; neural network; polyphonic music; Adaptive filters; Automation; Frequency estimation; Hidden Markov models; Instruments; Iterative algorithms; Mechatronics; Neural networks; Power harmonic filters; Trajectory; comb filter; music transcription; neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Automation, 2007. ICMA 2007. International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-0828-3
Electronic_ISBN :
978-1-4244-0828-3
Type :
conf
DOI :
10.1109/ICMA.2007.4303965
Filename :
4303965
Link To Document :
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