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Intelligent Audio Analysis pp 139–147Cite as

Audio Source Separation

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Part of the book series: Signals and Communication Technology ((SCT))

Abstract

In order to enhance the (audio) signal of interest in the case of added audio sources, one can aim at their separation. Albeit being very demanding, Audio Source Separation of audio signals has many interesting applications: for example, in Music Information Retrieval, it allows for polyphonic transcription or recognition of lyrics in singing after decomposing the original recording into voices and/or instruments such as drums or guitars, or vocals, e.g., for ’query by humming’. Here, non-negative matrix factorisation-based (NMF) approaches are explained. Further, ’NMF Activation Features’ are introduced and exemplified in the speech processing domain.

I just wondered how things were put together. —Claude Elwood Shannon.

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Authors and Affiliations

  1. LS für Mensch-Maschine-Kommunikation, TU München, Arcisstr. 21, 80290, München, Germany

    Björn Schuller

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  1. Björn Schuller
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Correspondence to Björn Schuller .

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Schuller, B. (2013). Audio Source Separation. In: Intelligent Audio Analysis. Signals and Communication Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36806-6_8

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  • DOI: https://doi.org/10.1007/978-3-642-36806-6_8

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  • Print ISBN: 978-3-642-36805-9

  • Online ISBN: 978-3-642-36806-6

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