Speaker recognition is a major task when security applications through speech input are needed. Nevertheless, speech variability is a main degradation factor in speaker recognition tasks. Both intra-speaker and external variability sources produce mismatch between training and testing phases. In this contribution, channel and inter-session variability are explored in order to accomplish real automatic systems for both commercial and forensic speaker recognition. Results are presented making use of "AHUMADA", a subset of "GAUDI" large speaker recognition-oriented database in Spanish.


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    Title :

    Speech variability in automatic speaker recognition systems for commercial and forensic purposes


    Contributors:

    Published in:

    Publication date :

    2000-11-01


    Size :

    461939 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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