Abstract
In this paper we suggest to apply a new feature, called Minimum Energy Density (MED), in discrimination of audio signals between speech and music. Our method is based on the analysis of local energy for 1 or 2.5 seconds audio signals. An elementary analysis of the probability for the power distribution is an effective tool supporting the decision making system. We compare our feature with Percentage of Low Energy Frames (LEF), Modified Low Energy Ratio (MLER) and examine their efficiency for two separate speech/music corpora.
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Kacprzak, S., Ziółko, M. (2013). Speech/Music Discrimination via Energy Density Analysis. In: Dediu, AH., Martín-Vide, C., Mitkov, R., Truthe, B. (eds) Statistical Language and Speech Processing. SLSP 2013. Lecture Notes in Computer Science(), vol 7978. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39593-2_12
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DOI: https://doi.org/10.1007/978-3-642-39593-2_12
Publisher Name: Springer, Berlin, Heidelberg
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