Abstract
In this paper, we introduce a method which uses a note model and signal post processing for a musical instrument to make a piece of music. one of the important issues in note transcription is extraction of multiple pitches. Most of the examined methods face error in joint harmonics and frequencies. A good model for note of a specified musical instrument can help us identify a note better. The presented method is based on wavelet transform, onset detection, note model and conformity reduction error algorithm or regression and post-processing for improved result. The results obtained show that detecting musical notes in a piece played on the guitar is, in comparison with similar methods, of higher detection accuracy and even in the case of noisy sound signals, the results are more acceptable.
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© 2009 Springer-Verlag Berlin Heidelberg
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Azizi, A., Faez, K., Delui, A.R., Rahati, S. (2009). Automatic Music Transcription Based on Wavelet Transform. In: Huang, DS., Jo, KH., Lee, HH., Kang, HJ., Bevilacqua, V. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2009. Lecture Notes in Computer Science, vol 5754. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04070-2_18
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DOI: https://doi.org/10.1007/978-3-642-04070-2_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04069-6
Online ISBN: 978-3-642-04070-2
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