Imposter Modelling Techniques for Speaker Verification based on Probabilistic Neural Networks

T. Ganchev, N. Fakotakis, and G. Kokkinakis (Greece)


Speech Processing, Pattern Recognition, Impostor Model ling, Speaker Verification, Probabilistic Neural Networks


The impact of two different impostor modelling tech niques on the performance of a Probabilistic Neural Net works (PNNs)-based text-independent speaker verifica tion system is studied. Depending on the technique used for background codebook construction, two versions of the system are obtained: with one universal background codebook, common to all authorized speakers, and with an individual speaker-dependent background codebook for each enrolled speaker. In particular, telephone-service applications over fixed and mobile telephone links with up to 500 users and short training times are considered. Results from experiments carried out on the SpeechDat(II)-FDB5000-Greek and the SpeechDat(M)-MDB1000-English corpora, with training times as short as 30 seconds and testing trials of about three seconds of voiced speech, are reported.

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