Abstract
This research proposes an automatic transcription-feedback system of music which help people to learn musical instruments by themselves. The focus of this research is piano. We develop real-time polyphonic pitch detectionfeedback system. For ’polyphonic pitch detection’, we use inner product based similarity measure with discriminant note detection threshold and top down attention. Also, we develop two parallel processes on simulink and matlab separately for real-time system. On simulink workspace, real-time recording and signal flow management is implemented. This system takes 2mins. 12secs. for analyzing 1min. piece and have accuracy of pitch detection as 79.33% for test case (Chopin Nocturne Op.9 N.2).
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© 2012 Springer-Verlag Berlin Heidelberg
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Kim, Gm., Kim, Ch., Lee, Sy. (2012). Implement Real-Time Polyphonic Pitch Detection and Feedback System for the Melodic Instrument Player. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7666. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34478-7_18
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DOI: https://doi.org/10.1007/978-3-642-34478-7_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34477-0
Online ISBN: 978-3-642-34478-7
eBook Packages: Computer ScienceComputer Science (R0)