Discrimination power weighted subword-based speaker verification

Since the discriminative powers of different phones vary, weighting techniques can be applied to bias the log-likelihood ratio of different phone segments to emphasize the more discriminating phones. First, we derive a Kullback-Leibler distance-based phone log-likelihood weighting scheme that incorporates the duration information. Second, we propose a posterior probability transformation method such that contributions from different phones are weighted implicitly according to their discrimination power. Using the two proposed approaches reduces speaker verification equal error rate by more than 10% on the YOHO database.