Fragmentation and Frontier Evolution for Genetic Algorithms Optimization in Music Transcription

Fonseca, Nuno; Rocha, Ana Paula

doi:10.1007/978-3-540-88309-8_45

Cited by 1 publication

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“…Each 30 second music fragment is splitted into 20 fragments of 1.5 seconds, the algorithm transcribes each fragment and then merge each fragment solution into a global solution (similarly with the Parisian approach [5] and with the system proposed by Fonseca [6]). Finally, in order to solve the frontier issues between fragmens, an hillclimber is applied on the notes near the fragment borders, as proposed by Fonseca [6]. To increase the performance, the algorithm employed in each fragment is based on the Gene Fragment Competion [3] approach.…”

Section: Methodsmentioning

confidence: 99%

Genetic Algorithm Approach to Polyphonic Music Transcription

Reis

Fonseca

Ferndandez

2007

2007 IEEE International Symposium on Intelligent Signal Processing

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This paper describes our method, submitted to MIREX 2008 task "Multiple Fundamental Frequency Estimation & Tracking". This task restricted the problem of Multiple F0 Estimation and Tracking to three cases: i) Estimate active fundamental frequencies on a frame-by-frame basis; ii) Track note contours on a continuous time basis (as in audio-tomidi); iii) Track timbre on a continuous time basis. The presented method is the first genetic algorithm approach to multi-timbral music transcription and is based on a previously published genetic algorithm approach for automatic music transcription originally designed to transcribe piano songs. This algorithm was adopted to support different timbres.

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Section: Methodsmentioning

confidence: 99%