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DSD100曲目数据集

DSD100曲目数据集

14.2G
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Music Analysis Audio

数据结构 ? 14.2G

    Data Structure ?

    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md

    Drawing

    The dsd100 is a dataset of 100 full lengths music tracks of different styles along with their isolated drums, bass, vocals and others stems.

    dsd100 contains two folders, a folder with a training set: "train", composed of 50 songs, and a folder with a test set: "test", composed of 50 songs. Supervised approaches should be trained on the training set and tested on both sets.

    For each file, the mixture correspond to the sum of all the signals. All signals are stereophonic and encoded at 44.1kHz.

    The data from dsd100 consist of 100 tracks which are derived from The 'Mixing Secrets' Free Multitrack Download Library. Please refer to this original resource for any question regarding your rights on your use of the DSD100 data.

    Have a look at the detailed list of all tracks.

    Download

    Parsers

    • dsdtools: Python based dataset parser
    • dsd100mat: MATLAB scripts to parse and process dsd100.

    Evaluation

    • bsseval: Matlab bases evaluation
    • SiSEC 2016: Signal Separation Evaluation Challenge 2016

    Acknowledgements

    We would like to thank Mike Senior not only for giving us the permission to use this multitrack material, but also for maintaining such resources for the audio community.

    Authors

    • Zafar Rafii
    • Antoine Liutkus
    • Fabian-Robert St?ter
    • Stylianos Ioannis Mimilakis

    Citation

    If you use this dataset, please reference it accordingly:

    @inproceedings{
      SiSEC16,
      Title = {The 2016 Signal Separation Evaluation Campaign},
      Address = {Cham},
      Author = {Liutkus, Antoine and St{"o}ter, Fabian-Robert and Rafii, Zafar and Kitamura, Daichi and Rivet, Bertrand and Ito, Nobutaka and Ono, Nobutaka and Fontecave, Julie},
      Editor = {Tichavsk{'y}, Petr and Babaie-Zadeh, Massoud and Michel, Olivier J.J. and Thirion-Moreau, Nad{`e}ge},
      Pages = {323--332},
      Publisher = {Springer International Publishing},
      Year = {2017},
      booktitle = {Latent Variable Analysis and Signal Separation - 12th International Conference, {LVA/ICA} 2015, Liberec, Czech Republic, August 25-28, 2015, Proceedings},
    }
    
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