Automatic Music Detection in Television Productions.
Sprache des Titels:
Proceedings of the International Conference on Digital Audio Effects (DAFx 07) , Bordeaux, France.
This paper presents methods for the automatic detection of music
within audio streams, in the fore- or background. The problem
occurs in the context of a real-world application, namely, the analysis
of TV productions w.r.t. the use of music. In contrast to plain
speech/music discrimination, the problem of detecting music in
TV productions is extremely difficult, since music is often used
to accentuate scenes while concurrently speech and any kind of
noise signals might be present. We present results of extensive experiments
with a set of standard machine learning algorithms and
standard features, investigate the difference between frame-level
and clip-level features, and demonstrate the importance of the application
of smoothing functions as a post-processing step. Finally,
we propose a new feature, called Continuous Frequency Activation
(CFA), especially designed for music detection, and show experimentally
that this feature is more precise than the other approaches
in identifying segments with music in audio streams.