hackerpeter1/SVQTD

Data Request instructions are in the project page here.

Dataset preparation

1. download youtube videos with a python script and convert to audios using ffmpeg
2. performing music source separation based on spleeter
3. energy-based segmentation, reference code can be found in ./split.py
4. extracting feature set using OPENSMILE (optional, only if you are interested in training with traditional feature set)

Training files

• Some pooling method for recognition neural network can be found in ./modules.
• Some models are in ./models.
• Some config files for respectively training Transformer and ResNet are in ./config.
• ./E2E.py can be used to train neural networks based on config files.
• ./RPSVM.py can be used to extract embeddings and train a SVM classifier using them.
• ./FSSVM.py can be used to train a SVM classifier using features from ComParE feature set.

Since our code is not user-friendly, if you have any questions about dataset downloading or the training code, please feel free to contact me through yanze.xu@outlook.com. Also welcome to talk with me if you are interested in timbre phenoemena.