Abstract:

To improve the precision of speaker indexing, an algorithm of speaker indexing based on gender is proposed by modifying BIC which is often used in speaker change criterion and by using gender information. In the first step, penalty distance is proposed to judge whether a speaker changes, which settles the problem that it is needed  to tune the penalty factor of the Bayesian information criterion(BIC) repeatedly by the speaker change criterion. In the second step, a gender model is used to judge every speaker’s gender on the basis of speaker changes. In the third step, speaker model bootstrapping is used to identify a male speaker or a female speaker separately. The experimental results show that: it is unnecessary to tune the penalty factor compared to BIC and F1 is improved by 2% compared to DISTBIC by the  speaker change detection; the speaker indexing accuracy is improved by 20.93% and the accuracy on the number of speakers is improved by 3% by using the gender information in speaker identification.

Key words: speaker indexing;gender information;speaker model bootstrapping