
handle: 10356/90747 , 10220/4705
In this paper, two different methods to implement one particular aspect of music transcription – musical note recognition – are presented. Both methods make use of existing algorithms in the form of the Constant-Q Transform (CQT) and the Discrete Wavelet Transform (DWT). Each existing algorithm is modified or extended so that a musical note recognition algorithm can be implemented on computer. Two main principles behind each method are peak detection using suitable thresholds and check for presence of harmonics in the process of note identification. The CQTbased method has a higher degree of accuracy, as it is able to resolve up to four simultaneous notes played on a guitar. The DWT-based method is less accurate but some suggestions are given as to how the algorithm can be further modified for improved performance.
Accepted version
DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
