B. Lehner, Gerhard Widmer,
"Monaural Blind Source Separation in the Context of Vocal Detection"
: Proceedings of the 16th International Society for Music Information Retrieval Conference, 10-2015
Original Titel:
Monaural Blind Source Separation in the Context of Vocal Detection
Sprache des Titels:
Englisch
Original Buchtitel:
Proceedings of the 16th International Society for Music Information Retrieval Conference
Original Kurzfassung:
In this paper, we evaluate the usefulness of several monaural
blind source separation (BSS) algorithms in the context
of vocal detection (VD). BSS is the problem of recovering
several sources, given only a mixture. VD is the problem of
automatically identifying the parts in a mixed audio signal,
where at least one person is singing. We compare the results
of three different strategies for utilising the estimated
singing voice signals from four state-of-the-art source separation
algorithms. In order to assess the performance of
those strategies on an internal data set, we use two different
feature sets, each fed to two different classifiers. After
selecting the most promising approach, the results on two
publicly available data sets are presented. In an additional
experiment, we use the improved VD for a simple postprocessing
technique: For the final estimation of the source
signals, we decide to use either silence, or the mixed, or the
separated signals, according to the VD. The results of traditionally
used BSS evaluation methods suggest that this is
useful for both the estimated background signals, as well
as for the estimated vocals.
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