By Topic

Bispectrum features for robust speaker identification

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
S. Wenndt ; Rome Lab., IRAA, Rome, NY, USA ; S. Shamsunder

Along with the spoken message, speech contains information about the identity of the speaker. Thus, the goal of speaker identification is to develop features which unique to each speaker. This paper explores a new feature for speech and shows how it can be used for robust speaker identification. The results are compared to the cepstrum feature due to its widespread use and success in speaker identification applications. The cepstrum, however, has shown a lack of robustness in varying conditions, especially in a cross-condition environment where the classifier has been trained with clean data but then tested on corrupted data. Part of the bispectrum is used as a new feature and we demonstrate its usefulness in varying noise settings

Published in:

Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on  (Volume:2 )

Date of Conference:

21-24 Apr 1997