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-----------COPYRIGHT NOTICE STARTS WITH THIS LINE------------
Copyright (c) 2017 Tampere University of Technology and its licensors
All rights reserved.
Permission is hereby granted, without written agreement and without
license or royalty fees, to use and copy the code for the MaD TwinNet
method/architecture, present in the GitHub repository with the identifier
mad-twinnet, (“Work”) described in the paper with title "MaD TwinNet: Masker-Denoiser
Architecture with Twin Networks for Monaural Sound Source Separation" (and
available also from https://arxiv.org/abs/1802.00300)
and composed of files with code in the Python programming language. This
grant is only for experimental and non-commercial purposes, provided that
the copyright notice in its entirety appear in all copies of this Work, and
the original source of this Work, (Audio Research Group, Lab. of Signal Processing)
at Tampere University of Technology, is acknowledged in any publication that
reports research using this Work.
Any commercial use of the Work or any part thereof is strictly prohibited.
Commercial use include, but is not limited to:
- selling or reproducing the Work
- selling or distributing the results or content achieved by use of the Work
- providing services by using the Work.
IN NO EVENT SHALL TAMPERE UNIVERSITY OF TECHNOLOGY OR ITS LICENSORS BE LIABLE TO
ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES
ARISING OUT OF THE USE OF THIS WORK AND ITS DOCUMENTATION, EVEN IF TAMPERE
UNIVERSITY OF TECHNOLOGY OR ITS LICENSORS HAS BEEN ADVISED OF THE POSSIBILITY
OF SUCH DAMAGE.
TAMPERE UNIVERSITY OF TECHNOLOGY AND ALL ITS LICENSORS SPECIFICALLY DISCLAIMS
ANY WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE WORK PROVIDED HEREUNDER
IS ON AN "AS IS" BASIS, AND THE TAMPERE UNIVERSITY OF TECHNOLOGY HAS NO OBLIGATION
TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
-----------COPYRIGHT NOTICE ENDS WITH THIS LINE------------