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- W2183678600 abstract "Automatic music transcription is the process of extracting musical information from an audio recording. It has many applications such as sheet music publishing and music visualisation for education or composition. This paper focuses on identifying the various ensembles of notes that occur in polyphonic mixtures. The method proposed utilises instrument specific note models to iteratively infer the presence of difference notes at the time of note onset. Preliminary results show that this method is well suited for the task and the system outputs a relative percentage of contribution for each of the individual note present in the spectrum. The use of note models creates a computationally inexpensive and robust system that can be calibrated to identify note characteristics from different instruments. It offers superior accuracy as opposed to having just a single instrument model for all notes as the spectral characteristics are non-stationary across the playable range for real instruments." @default.
- W2183678600 created "2016-06-24" @default.
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- W2183678600 date "2012-01-01" @default.
- W2183678600 modified "2023-09-26" @default.
- W2183678600 title "Polyphonic Music Transcription" @default.
- W2183678600 hasPublicationYear "2012" @default.
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