Authors

Jean-Louis Durrieu

Organization

LTS5, EPFL

Date

2011-2012

Contact

http://www.durrieu.ch/research

Check also README_v2.pdf for updated documentation.

• Qt (http://qt.nokia.com, included in PyQt4 binaries, see below)
• Python (use EPD: http://www.enthought.com/products/epd.php)
• Numpy (included in EPD, http://numpy.scipy.org)
• Scipy (in EPD, http://www.scipy.org)
• Matplotlib (in EPD, http://matplotlib.sourceforge.net)
• PySide (in EPD, http://www.pyside.org)

python separateLeadGUI2.py

Typical run:

1. Open a file (through Menu or "Open File" button or drag and drop in the corresponding field)

   If desired, please precise a directory to which the program will write the resulting files, in the "Output Directory Suffix" line. Note that for now, the program will simply concatenate the given suffix with the full-path of the audio file (i.e. without the filename of that file).

2. Select desired parameters for the algorithm:
   • window length: the window size, for the analysis frames 0.04644s is a good choice for singing voice, @44100Hz. Consider longer windows for bass extraction.
   • min F0: the lowest fundamental frequency F0 candidate
   • max F0: the highest fundamental frequency F0 candidate
3. Launch first decomposition, by pushing "Load File" button.
4. Wait for the computations to be computed (on Linux, one might see the evolution of the display, not available for MacOSX or Win yet)

5. Once the program is responsive again, the main window shows the matrix of amplitudes, for each F0 candidate: it is a time-frequency representation of the signal, with x-axis as time axis, and y-axis as F0 frequency axis. For now, the time is indicated as the frame number (current step size between frames is 12.5% of window length), while the F0 scale is shown on a log2 scale, proportional to the Western Muscial scale. The different A notes (A2: 110Hz, A3: 220Hz, A4: 440Hz,...) are also displayed, for ease of use. For more details on the representation, see [Durrieu2011].

   The user should then select the time-frequency zones corresponding to the instrument she desires to separate. The provided matrix of amplitude should help deciding and identifying these regions. When the user clicks, and moves the mouse while left button is pressed, the selected region corresponds to the line described by the mouse, and all the points between that line plus and minus half a semitone. These regions are shown as red delimited contours.

   The user can zoom in the picture and move around thanks to the top toolbar. Note however that each time after using these tools, she needs to deactivate them again (by clicking again on the corresponding button) in order to be able to proceed with the source selection. She can also modify the display normalization, between 3 modes: no-normalization (displays the actual values in dB scale), normalizing each frame by the maximum value, or by the sum of all values. The minimum and maximum values to set the color scale can also be modified.

   Note also that the possibility of going back in the annotation is under development. For now, the user can already choose the button "Delete", and going over the previously selected zones will "deselect" them.

   If the application is separateLeadGUIControlsPlay.py, then the user can also have an audio feedback corresponding to the displayed time-range, by clicking on the image with the mouse right-button.

6. Once satisfied with the selected regions, the user should click the "Separate" button, which will launch the estimation of the separated sources, given the user input.

   Alternatively, the user could also push the "Separate (Melody)" button, which discards the user selected areas and, instead, automatically detects the most prominent melody line, as published in our previous works [Durrieu2010].

The author would be greatful if the testers could provide some feedback. More specifically, some ergonomy issues encountered would be welcome, for instance:

• audio feedback required (for now, we advice the use of Audacity).
• better aspect for selected (and even more de-selected) areas.
• adequation of the frequency scale for musicians/non-musicians?
• readability of the representation?

• The Phonon module has been added, but the playback on Linux is not smooth.
• The "right click to play" is somehow conflicting with the pan/zoom tool (right click + move allows the zooming tool on the image, and will start or stop the playback)

• The interface may be a bit slow, sometimes, because, under the hood, each time the user changes the colormap range, or selects new regions, quite some computation is going on (matplotlib contours and set_clim stuff).