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    Detection of Target Speakers in Audio Databases

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    Author
    Magrin-Chagnolleau, Ivan; Rosenberg, Aaron; Parthasarathy, S.
    Date
    2004-01-14
    Abstract
    The problem of speaker detection in audio databases is addressed in this paper. Gaussian mixture modeling is used to build target speaker and background models. A detection algorithm based on a likelihood ratio calculation is applied to estimate target speaker segments. Evaluation procedures are defined in detail for this task. Results are given for different subsets of the HUB4 broadcast news database. For one target speaker, with the data restricted to high quality speech segments, the segment miss rate is approximately 7%. For unrestricted data, the segment miss rate is approximately 27%. In both cases the segment false alarm rate is 4 or 5 per hour. For two target speakers with unrestricted data, the segment miss rate is approximately 63% with about 27 segment false alarms per hour. The decrease in performance for two target speakers is largely associated with short speech segments in the two target speaker test data which are undetectable in the current configuration of the detection algorithm.
    Description
    Conference Paper
    Citation
    I. Magrin-Chagnolleau, A. Rosenberg and S. Parthasarathy, "Detection of Target Speakers in Audio Databases," 1999.
    Published Version
    http://dx.doi.org/10.1109/ICASSP.1999.759797
    Keyword
    Temporary; Signal Processing Applications; Temporary
    Type
    Conference paper
    Citable link to this page
    https://hdl.handle.net/1911/20077
    Metadata
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    • DSP Publications [508]
    • ECE Publications [1468]

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    Managed by the Digital Scholarship Services at Fondren Library, Rice University
    Physical Address: 6100 Main Street, Houston, Texas 77005
    Mailing Address: MS-44, P.O.BOX 1892, Houston, Texas 77251-1892
    Site Map