文件列表:

LICENSE (1816, 2018-04-27)
audio_files (0, 2018-04-27)
audio_files\.dummy.txt (40, 2018-04-27)
dataset (0, 2018-04-27)
dataset\.dummy.txt (40, 2018-04-27)
functions (0, 2018-04-27)
functions\GetSDR.m (1775, 2018-04-27)
functions\NMF.m (2188, 2018-04-27)
functions\STFT.m (1033, 2018-04-27)
functions\cnmf_wisa.m (2381, 2018-04-27)
functions\complex_ISNMF_unconstrained.m (3847, 2018-04-27)
functions\complex_betaNMF.m (3101, 2018-04-27)
functions\get_data_DSD_cbetanmf.m (1371, 2018-04-27)
functions\iSTFT.m (1501, 2018-04-27)
functions\wiener_nmf.m (397, 2018-04-27)
metrics (0, 2018-04-27)
metrics\.dummy.txt (40, 2018-04-27)
scripts (0, 2018-04-27)
scripts\compute_score_cbetanmf.m (1543, 2018-04-27)
scripts\learning_beta_cbnmf.m (2823, 2018-04-27)
scripts\separation_cbetanmf.m (2407, 2018-04-27)
scripts\set_settings_cbetanmf.m (458, 2018-04-27)

# Complex NMF with the beta-divergence GitHub repository Code for complex NMF with the beta-divergence Here, you will find the code related to complex NMF with the beta-divergence. It is applied to the task of harmonic/percussive source separation. If you use any of the things existing in this repository, please cite the [corresponding paper](https://hal.archives-ouvertes.fr/hal-017796***). ### Dataset set-up To reproduce the experiments conducted in our paper, you will need to download the [Dexmixing Secret Database (DSD100)](http://www.sisec17.audiolabs-erlangen.de) and to place its content in the `dataset`. If you use this dataset, you will end up with the proper directory structure and file names, as used in the `functions/get_data_DSD_cbetanmf` function. If you want to use a different dataset, then you have two options: - either you format your file names and directory structure to match the one from DSD100; - or you modify the file reading function `get_data_DSD_cbetanmf` to suit your needs. ### Experiments The two main scripts to reproduce the experiments are in the `scripts` folder: `learning_beta_cbnmf` will perform a grid search for beta and plot the separation quality (SDR, SIR and SAR) as a function of this parameter. This apply for Complex NMF and NMF. `separation_cbetanmf` will perform the benchmark conducted in the paper, that is, comparing NMF and complex NMF with Euclidean, IS and beta divergences. The audio files will be record in the `audio_files` folder and the script `comopute_score_cbetanmf` computes the SDR, SIR and SAR for this benchmark.

近期下载者：

相关文件：

评论：[我要评论] [举报此文件]

收藏者：