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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