%% Part-2 Tutorial on Singing Transcription (by <http://mirlab.org/jang Roger Jang>)
%%
% This is the part-2 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 MATLAB functions for singing transcription.
% You should have read <goTutorial01.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
%% Basic operations
% In the <goTutorial01.html part-1 tutorial>, we have save "pv" and "note" of the
% first phrase of the Youtube video of <https://www.youtube.com/watch?v=be2wvNFTLMc Áô§Îªº¯Í»H>.
% Now we can load the saved file for further processing:
load transparentWings.mat
noteGt=note;
%%
% You can play the PV of the first phrase:
opt=pvPlay('defaultOpt');
opt.method=2;
figure; pvPlay(pv, opt, 1);
%%
% You can play the groundtruth note of the first phrase:
fprintf('Play the groundtruth music notes...\n');
opt=notePlay('defaultOpt');
opt.auFileName='note.wav';
figure; notePlay(noteGt, opt, 1);
%%
% Now we can try to segment the singing pitch vector into notes.
% First of all, we can cut PV into segments based on where the silence occurs.
% Note that the transition from silence (with zero pitch) to non-silence
% (with nonzero pitch) indicates the onset of a note.
% Each segment could contain several notes.
% However, for simplicity, we can assume each segment corresponds to a note.
% This simple method is specified by 'simple00', as follows. 
opt=pv2note('defaultOpt');
opt.method='simple00';
opt.gtNote=noteGt;
figure; notePredicted=pv2note(pv, opt, 1);
fprintf('No. of GT notes=%d\n', length(noteGt.pitch));
fprintf('No. of predicted notes=%d\n', length(notePredicted.pitch));;
fMeasure=noteVecSim(notePredicted, noteGt);
fprintf('fMeasure=%g\n', fMeasure);
%%
% If a segment contains large pitch variation, then this segment is likely
% to contains several music notes. We can use a simple criterion to cut a
% segment into notes whenever the pitch difference between neighboring
% frames is larger than 1 semitone.
% This method is specified by 'simple01', as follows:
opt=pv2note('defaultOpt');
opt.method='simple01';
opt.gtNote=noteGt;
figure; notePredicted=pv2note(pv, opt, 1);
fprintf('No. of GT notes=%d\n', length(noteGt.pitch));
fprintf('No. of predicted notes=%d\n', length(notePredicted.pitch));;
fMeasure=noteVecSim(notePredicted, noteGt);
fprintf('fMeasure=%g\n', fMeasure);
%% 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.