Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

Speaker verification under mismatched data conditions

Speaker verification under mismatched data conditions

For access to this article, please select a purchase option:

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Signal Processing — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

This study presents investigations into the effectiveness of the state-of-the-art speaker verification techniques (i.e. GMM–UBM and GMM–SVM) in mismatched noise conditions. Based on experiments using white and real world noise, it is shown that the verification performance offered by these methods is severely affected when the level of degradation in the test material is different from that in the training utterances. To address this problem, a modified realisation of the parallel model combination (PMC) method is introduced and a new form of test normalisation (T-norm), termed condition adjusted T-norm, is proposed. It is experimentally demonstrated that the use of these techniques with GMM–UBM can significantly enhance the accuracy in mismatched noise conditions. Based on the experimental results, it is observed that the resultant relative improvement achieved for GMM–UBM (under the most severe mismatch condition considered) is in excess of 70%. Additionally, it is shown that the improvement in the verification accuracy achieved in this way is higher than that obtainable with the direct use of PMC with GMM–UBM. Moreover, it is found that while the accuracy performance of GMM–SVM can also considerably benefit from the use of these techniques, the extensive computational cost involved in this case severely limits the use of such a combined approach in practice.

http://iet.metastore.ingenta.com/content/journals/10.1049/iet-spr.2008.0175
Loading

Related content

content/journals/10.1049/iet-spr.2008.0175
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address