This paper addresses the problem of evaluating effectiveness of musical sound separation algorithms. The standardized procedure for evaluating separation quality does not exist. The most convincing and typical way to do this is by carrying out subjective listening tests. However, subjective tests need a solid statistical validation, which means that many experts should take part in such tests, the room characteristics should be adequate, and what is also important, such tests are time consuming. Thus this paper attempts to show that it is possible to carry out the evaluation tests in an automatic way, by employing an Artificial Network System (ANN), which is further justified by experts’ opinion.
Click to purchase paper as a non-member or you can login as an AES member to see more options.
No AES members have commented on this paper yet.
To be notified of new comments on this paper you can
subscribe to this RSS feed.
Forum users should login to see additional options.
If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.
