%% Part-2 Tutorial on Singing Transcription (by <http://mirlab.org/jang Roger Jang>)
%%
% This is the part-3 tutorial on singing transcription from polyphonic music, for <https://aidea-web.tw/topic/bfcaa1b4-5b69-4f17-a5c4-f58ef7da68cb AI Cup Competition>.
% This part will focus on evaluation on singing transcription.
% You should have read <goTutorial.html part-1 tutorial> and <goTutorial02.html part-2 tutorial> before reading this part.
%% Preprocessing
% Before we start, let's add necessary toolboxes to the search path of MATLAB:
addpath d:/users/jang/matlab/toolbox/utility
addpath d:/users/jang/matlab/toolbox/sap
addpath d:/users/jang/matlab/toolbox/machineLearning
%%
% All the above toolboxes can be downloaded from <http://mirlab.org/jang/matlab/toolbox Roger's toolbox page>.
% Make sure you are using the latest toolboxes to work with this script.
%%
% For compatibility, here we list the platform and MATLAB version that we used to run this script:
fprintf('Platform: %s\n', computer);
fprintf('MATLAB version: %s\n', version);
fprintf('Date & time: %s\n', char(datetime));
scriptStartTime=tic;	% Timing for the whole script
%% ST evaluation of a song
% Here we want to focus on the evaluation of singing transcription on a single song.
% We have put every component for doing so in a file "goTestOne.m", as follows:
type goTestOne.m
%%
% We can run the above script to see how it goes:
goTestOne
%% ST evaluation of MIR-ST500 dataset
% Then we can perform the evaluation over all songs in MIR-ST500 dataset, as follows:

% Get all groundtruth files
melody=dir('d:/dataSet/public/MIR-ST500/*/*_groundtruth.txt');
melodyCount=length(melody);
fprintf('melodyCount=%d\n', melodyCount);
% Get song ID
for i=1:melodyCount
	items=split(melody(i).name, '_');
	melody(i).songId=eval(items{1});
end
% Ordered by songID
songId=[melody.songId];
[sorted, index]=sort(songId);
melody=melody(index);
% Read each feature file and perform singing transcription
myTic=tic;
for i=1:melodyCount
	gtFilePath=fullfile(melody(i).folder, melody(i).name);
	% Read the groundtruth
	melody(i).noteGt=noteFileRead(gtFilePath);
	% Read the feature file
	feaFilePath=fullfile(melody(i).folder, sprintf('%d_feature.json', melody(i).songId));
	fea=jsondecode(fileread(feaFilePath));
	pv.pitch=fea.vocal_pitch;
	pv.time=fea.time;
	melody(i).notePredicted=pv2note(pv, opt);
	melody(i).fMeasure=noteVecSim(melody(i).notePredicted, melody(i).noteGt);
	fprintf('%d/%d: file=%s, f-measure=%g\n', i, melodyCount, gtFilePath, melody(i).fMeasure);
end
fprintf('Time for pv2note() and noteVecSim(): %g sec\n', toc(myTic));
fprintf('Overall f-measure=%g\n', mean([melody.fMeasure]));
%%
% Since the above procedure will be invoked many times for iterative
% performance optimization, we shall use several function to finish the
% above task. First of all, let's read the dataset all at once:
dsDir='d:/dataSet/public/MIR-ST500';
[melody, time]=stDsRead(dsDir);		% Read the dataset
fprintf('Time for reading "%s" = %g sec\n', dsDir, time);
%%
% Then we can try to do note detection:
opt=stDsPredict('defaultOpt');
[melody02, time]=stDsPredict(melody, opt, 1);	% Evaluate the performance
fprintf('Elapsed time=%g sec.\n', time);
%%
% Then we can start performance evaluation:
opt=stDsPerfEval('defaultOpt');
[perf, time]=stDsPerfEval(melody02, opt, 1);	% Evaluate the performance
fprintf('Average f-measure=%g, elapsed time=%g sec.\n', perf, time);
%% Summary
% This is a brief tutorial on singing transcription.
% There are several directions for further improvement:
%
% * Explore other features from the original audio files
% * Use other models, such as LSTM, RNN, GRU, etc.
%
%% Appendix
% List of functions, scripts, and datasets used in this script:
%
% * <../list.asp List of files in this folder>
%
%%
% Date and time when finishing this script:
fprintf('Date & time: %s\n', char(datetime));
%%
% Overall elapsed time:
toc(scriptStartTime)
%%
% <http://mirlab.org/jang Jyh-Shing Roger Jang>, created on
datetime
%%
% If you are interested in the original MATLAB code for this page, you can
% type "grabcode(URL)" under MATLAB, where URL is the web address of this
% page.