ADTLib

Automated Drum Transcription Library
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README.md (2801B)

      1 # Automatic Drum Transcription Library (ADTLib)
      2 
      3 The automatic drum transcription (ADT) library contains open source ADT algorithms to aid other researchers in areas of music information retrieval (MIR). The algorithms return both a .txt file of kick drum, snare drum, and hi-hat onsets and an automatically generated drum tabulature. 
      4 
      5 ### Browser Version (ADTWeb)
      6 
      7 [ADTWeb](http://dmtlab.bcu.ac.uk/ADT/): a browser based version of ADTLib is now available. 
      8 
      9 ## License
     10 
     11 This library is published under the BSD license which allows redistribution and modification as long as the copyright and disclaimers are contained. The full license information can be found on the [license](https://github.com/CarlSouthall/ADTLibNew/blob/master/LICENSE.txt) page. 
     12 
     13 ## Installation
     14 
     15 #### Required Packages
     16 
     17 • [numpy](https://www.numpy.org)   
     18 • [scipy](https://www.scipy.org)   
     19 • [madmom](https://github.com/CPJKU/madmom)   
     20 • [tensorflow](https://www.tensorflow.org/)  
     21 • [fpdf](https://pyfpdf.readthedocs.io/en/latest/) (for tab creation)
     22 
     23 The easiest and suggested method to install the library is to use pip:
     24 
     25      pip install ADTLib
     26 
     27 To update the library use:
     28 
     29      pip install --upgrade ADTLib
     30      
     31 ## Usage
     32 
     33 Algorithms contained within the library are both available as functions for use within python and as command line executable programmes.
     34 
     35 ### Examples 
     36 
     37 #### Command line 
     38 
     39     ADT Drum.wav
     40 
     41 
     42 #### Python function
     43 
     44 ```Python
     45 from ADTLib import ADT
     46 
     47 out=ADT(['Drum.wav'])
     48 ```
     49 
     50 See the [usage](https://github.com/CarlSouthall/ADTLibNew/blob/master/usage.md) page for more information.
     51 
     52 ## References
     53 
     54 
     55 | **[1]** |                  **[Southall, C., R. Stables, J. Hockman, Automatic Drum Transcription Using Bi-directional Recurrent                    Neural  Networks, Proceedings of the 17th International Society for Music Information Retrieval Conference (ISMIR), 2016.](https://carlsouthall.files.wordpress.com/2017/12/ismiradt2016.pdf)**|
     56 | :---- | :--- |
     57 
     58 | **[2]** |                  **[Southall, C., R. Stables, J. Hockman, Automatic Drum Transcription For Polyphonic Recordings Using Soft Attention Mechanisms and Convolutional Neural Networks, Proceedings of the 18th International Society for Music Information Retrieval Conference (ISMIR), 2017.](https://carlsouthall.files.wordpress.com/2017/12/ismir2017adt.pdf)**|
     59 | :---- | :--- |
     60 
     61 | **[3]** |                  **[Southall, C., N. Jillings, R. Stables, J. Hockman, ADTWeb: An Open Source Browser Based Automatic Drum Transcription System. Proceedings of the 18th International Society for Music Information Retrieval Conference (ISMIR), 2017.](https://carlsouthall.files.wordpress.com/2017/12/ismir2017adtweb.pdf)**|
     62 | :---- | :--- |
     63 
     64 ## Help
     65 
     66 Any questions please feel free to contact me on [email protected]
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