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.
Speech variability in automatic speaker recognition systems for commercial and forensic purposes
IEEE Aerospace and Electronic Systems Magazine ; 15 , 11 ; 27-32
2000-11-01
461939 byte
Article (Journal)
Electronic Resource
English
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