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1 %% Multichannel audio source separation evaluation framework (MASSEF)
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2 %
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3 %% Overview
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4 %
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5 % <<../MASSEF.png>>
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6 %
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7 % The multichannel audio source separation evaluation framework is designed
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8 % to facilitate the development and evaluation of audio source separation
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9 % algorithms. The framework generates the mixture(s), provides the
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10 % mixture(s) to the separation algorithm(s), and evaluates the outputs of
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11 % the separation algorithm(s). The framework can also calculate and
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12 % evaluate the ideal masks for the purposes of comparison.
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13 %
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14 % Sources may have any number of channels; the framework evaluates each
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15 % channel. The use of <matlab:doc('iosr.bss.mixture') |iosr.bss.mixture|>
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16 % objects facilitate the evaluation of spatialised mixtures (e.g.
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17 % binaural).
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18 %
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19 % The framework comprises two main classes:
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20 %
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21 % * <help_MASSEF.html MASSEF>—multichannel audio source separation
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22 % evaluation framework class.
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23 % * <help_MASSEFresults.html MASSEFresults>—the results class used by
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24 % MASSEF.
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25 %
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26 % <help_Example.html View an example of the use of these classes.>
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27 %
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28 % MASSEF can be used to evaluate and compare binaural separation algorithms,
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29 % provided that the algorithms conform to the <help_Separators.html
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30 % required format>.
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31 %
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32 %% Installation
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33 %
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34 % Before using the framework, you need to download and install its
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35 % dependencies. This can be done automatically using the
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36 % <help_MASSEF_install.html MASSEF.install()> method. Before each session,
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37 % MASSEF needs to be started using the <help_MASSEF_start.html
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38 % MASSEF.start()> method.
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39 %
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40 %% Usage
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41 %
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42 % The framework can be run in two ways:
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43 %
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44 % # by providing <matlab:doc('iosr.bss.mixture') |iosr.bss.mixture|>
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45 % objects and separation algorithms, or
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46 % # by providing estimate and true source wav files.
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47 %
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48 % If 1), the framework operates as described above. In addition, the
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49 % framework can:
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50 %
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51 % * evaluate localisation accuracy (if the algorithm performs localisation)
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52 % of any azimuth/elevation estimates returned by the algorithm, and
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53 % * evaluate time-frequency mask accuracy (if the algorithm calculates
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54 % one).
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55 %
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56 % Use the <help_MASSEF_execute.html MASSEF.execute()> method to operate in
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57 % this mode.
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58 %
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59 % If 2), the framework evaluates only the supplied estimate(s) using
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60 % signal-related metrics. Use the <help_MASSEF_evaluate.html
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61 % MASSEF.evaluate()> method to operate in this mode.
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62 %
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63 % <html>
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64 % <hr>
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65 % <p>Copyright © 2017 <a href="http://www.surrey.ac.uk">University of Surrey</a><br>
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66 % <a href="http://iosr.uk">Institute of Sound Recording, University of Surrey, UK</a></p>
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67 % </html>
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