Technical Program

Paper Detail

Paper:SP-P5.2
Session:Topics in Speech Coding
Time:Wednesday, May 19, 09:30 - 11:30
Presentation: Poster
Topic: Speech Processing: Speech Coding
Title: A DATA MINING APPROACH TO OBJECTIVE SPEECH QUALITY MEASUREMENT
Authors: Wei Zha; Queen's University 
 Wai-Yip Chan; Queen's University 
Abstract: Existing objective speech quality measurement algorithmsstill fall short of the measurement accuracy that can beobtained from subjective listening tests. We propose an approach that uses statistical data mining techniques to improve the accuracy of auditory-model based quality measurement algorithms. We present the design of a novel measurement algorithm using the multivariate adaptive regression splines (MARS) method. A large set of speech distortion features is first created. MARS is used to find a small set of features that provide the best estimate (''model'') of speech quality. One appeal of the approach is that the model size can scale with the amount of speech data available for learning. In our simulations, the new algorithm furnishes significant performance improvement over PESQ.
 
           Back


Home -||- Organizing Committee -||- Technical Committee -||- Technical Program -||- Plenaries
Paper Submission -||- Special Sessions -||- ITT -||- Paper Review -||- Exhibits -||- Tutorials
Information -||- Registration -||- Travel Insurance -||- Housing -||- Workshops

©2015 Conference Management Services, Inc. -||- email: webmaster@icassp2004.org -||- Last updated Wednesday, April 07, 2004