Various types of noise and other forms of degradation in the acoustic signal are typical of speech recordings used in forensic speaker recognition. The results of this study suggest that certain speech enhancement algorithms can be a useful tool for preprocessing speech samples before attempting automated recognition. This is particularly true for additive noise such as instrumental music and noise inside of a moving car. Comparing equal-error rates of identification experiments for ten male speakers based on the original, degraded, and enhanced voice signals, the performance of the speaker recognition system was most affected by pop music in both single-channel and 2-channel recordings. In contrast, road traffic and restaurant noise do not markedly degrade recognition performance.

Authors: Künzel, Hermann J.; Alexander, Paul
Affiliations: Dept. of Phonetics, University of Marburg, Marburg, Germany; Cedar Audio Ltd., Cambridge, UK(See document for exact affiliation information.)
JAES Volume 62 Issue 4 pp. 244-253; April 2014
Publication Date: April 16, 2014

Click to purchase paper as a non-member or you can login as an AES member to see more options.

No AES members have commented on this paper yet.

Subscribe to this discussion

To be notified of new comments on this paper you can subscribe to this RSS feed. Forum users should login to see additional options.

Start a discussion!

If you would like to start a discussion about this paper and are an AES member then you can login here:
Username:
Password:

If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.