Convolutive Blind Source Separation Methods

Michael Syskind Pedersen, Jan Larsen, Ulrik Kjems, Lucas C. Parra

    Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

    898 Downloads (Pure)

    Abstract

    During the past decades, much attention has been given to the separation of mixed sources, in particular for the blind case where both the sources and the mixing process are unknown and only recordings of the mixtures are available. In several situations it is desirable to recover all sources from the recorded mixtures, or at least to segregate a particular source. Furthermore, it may be useful to identify the mixing process itself to reveal information about the physical mixing system. In some simple mixing models each recording consists of a sum of differently weighted source signals. However, in many real-world applications, such as in acoustics, the mixing process is more complex. In such systems, the mixtures are weighted and delayed, and each source contributes to the sum with multiple delays corresponding to the multiple paths by which an acoustic signal propagates to a microphone. Such filtered sums of different sources are called convolutive mixtures. There are already a number of partial reviews available on this topic so the purpose of this chapter is to provide a complete survey of convolutive BSS and identify a taxonomy that can organize the large number of available algorithms. This may help practitioners and researchers new to the area of convolutive source separation obtain a complete overview of the field. Hopefully those with more experience in the field can identify useful tools, or find inspiration for new algorithms.
    Original languageEnglish
    Title of host publicationSpringer Handbook of Speech
    Number of pages1176
    VolumeChap. 52
    PublisherSpringer
    Publication date2008
    ISBN (Print)978-3-540-49125-5
    Publication statusPublished - 2008

    Keywords

    • ica
    • blind source separation
    • convolutive

    Fingerprint

    Dive into the research topics of 'Convolutive Blind Source Separation Methods'. Together they form a unique fingerprint.

    Cite this