By Topic

Reinforcement of MLLR speaker adaptation using optimal linear interpolation

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
$31 $31
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

1 Author(s)
Ing-Jr Ding ; Dept. of Electr. Eng., Nat. Formosa Univ., Huwei, Taiwan

An optimal linear interpolation scheme applied to MLLR speaker adaptation is presented. The proposed reinforced MLLR method, called αopt-MLLR, regulates the influence of MLLR adaptation when the training data from a new speaker is improper by adequately incorporating prior knowledge of the initial models into adaptation, and thus ensures the robustness of MLLR adaptation. The proposed mechanism is conceptually simple and computationally inexpensive, and is superior to FLC-MLLR in regard to lower computing cost.

Published in:

Electronics Letters  (Volume:48 ,  Issue: 5 )