73 research outputs found
Speaker recognition improvement using blind inversion of distortions
In this paper we propose the inversion of nonlinear
distortions in order to improve the recognition rates of a
speaker recognizer system. We study the effect of
saturations on the test signals, trying to take into account
real situations where the training material has been recorded
in a controlled situation but the testing signals present some
mismatch with the input signal level (saturations). The
experimental results shows that a combination of several
strategies can improve the recognition rates with saturated
test sentences from 80% to 89.39%, while the results with
clean speech (without saturation) is 87.76% for one
microphone
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