This is the folder for containing the code, dataset and supplement information of SMC 2016 paper "Pitch Contour Segmentation for Computer-aided Jingju Singing Training"

The code used in this paper is in "code" folder, where you can find:

1. melodic_transcription: code for estimating the bigram note transition probabilities from the jingju singing scores (dataset) and evaluating the performance of melodic transcription.
2. pitch_contour_segmentation: the python code for pitch contour segmentation without the "preliminary segmentation" step (which is already performed by using pyin_noteTransition).
3. pyin_noteTransition: the modified pYIN algorithm code incorporated with the jingju bigram note transition probabilities + the binary for Mac OS X.

The correct step to reproduce the results is: 1) install pyinBOBigram Vamp plugin in pyin_noteTransition, 2) evaluate the performance of melodic transcription, 3) evaluate the pitch contour segmentation.

The dataset used in this paper is in "dataset" folder. The a cappella singing audio recordings is not contained in this folder due to their large size, please contact the paper authors to request them (rong.gong@upf.edu). In the folder you can find:

1. groundtruth: the ground truth annotation for

• melodic transcription (male_12_pos_1 missing)
• parameter optimization,
• evaluating the StdCdLe thresholding and the overall segmentation performance.

2. jinging singing scores in .xml format used for estimating the bigram note transition probabilities.

In the folder "supplementary_information", you can find:

the complete grid search result for optimizing "StdCdLe threshold" and other parameters.