Close category search window
 

A vector-regression tree for generating energy contours

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 $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

3 Author(s)
Sangho Lee ; Dept. of Comput. Sci., Korea Adv. Inst. of Sci. & Technol., Seoul, South Korea ; Yeon-Jun Kim ; Yung-Hwan Oh

This letter presents a novel approach based on the vector-regression tree to generate energy contours. Given linguistic features, our approach predicts a vector containing ten sampled energy values for each phone by using a vector-regression tree, concatenates the vectors, and computes energy values at 10 ms intervals by linear interpolation. The correlation coefficient for the observed and predicted energy values with our approach was 0.78 on 200 test utterances, and a root mean squared error (RMSE) of 4.88 dB was obtained. This approach outperformed previous methods in objective measures.

Published in:
Signal Processing Letters, IEEE  (Volume:7 ,  Issue: 8 )

Date of Publication: Aug. 2000

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.