Using MMSE to improve session variability estimation
نویسندگان
چکیده
منابع مشابه
Using MMSE to improve session variability estimation
In this paper, the Session Variability Subspace Projection (SVSP) method based on model compensation for speaker verification was improved using the Minimum Mean Square Error (MMSE) criterion. The issue of SVSP is that the speaker’s session-independent supervector is approximated by the average of all his or her session-dependent GMM-supervectors when estimating SVSP matrix. However, the error ...
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• Proof: X is j G implies that V = uX is G with mean uμ and variance uΣu. Thus its characteristic function, CV (t) = e ituμe−t 2uTΣu/2. But CV (t) = E[e itV ] = E[e TX ]. If we set t = 1, then this is E[e TX ] which is equal to CX(u). Thus, CX(u) = CV (1) = e iuμe−u TΣu/2. • Proof (other side): we are given that the charac function ofX, CX(u) = E[eiuTX ] = e μe−u TΣu/2. Consider V = uX. Thus, C...
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ژورنال
عنوان ژورنال: International Journal of Biometrics
سال: 2010
ISSN: 1755-8301,1755-831X
DOI: 10.1504/ijbm.2010.035449