This reposiory contains the code for our course project for Machine Learning (CS419) at IIT Bombay. We have used the PyTorch library to construct a neural network to separate instruments from a music file. We have implemented the paper "Monoaural Audio Source Separation Using Deep Convolutional Neural Networks", along with a few modifications and experiments inspired by other papers.
- [16D100012] Sarthak Consul (@SConsul)
- [160110085] Archiki Prasad (@archiki)
- [16D070001] Parthasarathi Khirwadkar (@kparth98)
- [16D100001] Deepak Gopalan (@DeepakGopalan)
- [1] Pritish Chandna, M. Miron, Jordi Janer, and Emilia G´omez. Monoaural audio source separation using deep convolutional neural networks. In 13th International Conference on Latent Variable Analysis and Signal Separation (LVAICA2017), 02/2017 2017
- [2] E. Vincent, R. Gribonval, and C. Fevotte. Performance measurement in blind audio source separation. IEEE Transactions on Audio, Speech, and Language Processing, 14(4):1462–1469, July 2006
- [3] Chao Peng, Xiangyu Zhang, Gang Yu, Guiming Luo, and Jian Sun. Large kernel matters - improve semantic segmentation by global convolutional network. CoRR, abs/1703.02719, 2017