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matlab prototype for drum transcription sytem described in the paper https://drive.google.com/file/d/0B4bIMgQlCAuqdGVRbVNNbzJfeUU/view
georgid/DrumTranscriptionWithBarPointer
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%%%%% For preprocessing data see scripts in the ENST-public dir. %%%%% For whole process see. traindoit % preprocess annotation. does same as mergeDrumTypesENST but for an event within combination window % instead of one sd and one bd event with same timestamp, prints one comined event bd_sd combineDrumTypesENST(songURI) -> function called in trainPositionalProbs % output is .txt.combined %use timestamps in file *.notePart.combined for files %% training all. function traindoit NOTE: obs probs have to be trained as well after combineDrumTypesENST is run since this assures that the spectrum is taken of snare-only and bass-only hits % decode decodeAlgorithm( transMatrixFull, tableObsProbs, positionalProbs, V, P); % the logic for one iteration itself: function decode() 1. construct A table based on C. 2. construct B table - these give the model without the transitions. 3. summ over A velocities and multiply by B 4. take max drum type. %%% main logic of decoding. does write results of decoded sequence into file: transcr.pos - transcr.vel - transcr.sd transcr.bd doitOneSong() %%%%% evaluation: eval/evalPrecRecallForOneSong use mergeDrumTypesENST. % the file is .txt.bd and .txt.sd if using clasifier with combined classes consider its output as two detections of the two types (e.g. bd and sd): then compare the same way as with no combinations One can exlude MIDIs from training by commenting a code snippet in trainObsLiks and can exclude them from evaluation by commenting a code snippet in evalPrecRecallAllSongs ------------
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matlab prototype for drum transcription sytem described in the paper https://drive.google.com/file/d/0B4bIMgQlCAuqdGVRbVNNbzJfeUU/view
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