Neuro-fuzzy-based biometric system using speech features
by Anupam Shukla, Ritu Tiwari, Chandra Prakash Rathore
International Journal of Biometrics (IJBM), Vol. 2, No. 4, 2010

Abstract: Biometric identification is one of the most developing areas. In this paper, a biometric system is simulated using speech features, which identifies the speaker along with their gender and mental status. Work here is broadly classified into two parts, i.e., extraction of the speech features, namely Pitch, Amplitude, Number of Zero-Crossing (NZC), Average Power Spectral Density (PSD) content in the speech of informant and in the second part an adaptive neuro-fuzzy based simulation model has been developed for speaker identification along with their gender and mental status. The recognition score varies depending on different input and output Membership Functions (MFs).

Online publication date: Thu, 30-Sep-2010

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Biometrics (IJBM):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com