Paper Info
Title
Investigation on Adaptation Using Different Discriminative Training Criteria Based Linear Regression and Map
Abstract
This paper presents a comparison and evaluation between the conventional maximum likelihood estimation based adaptation and different discriminative adaptation criteria. The performance of different LR and MAP adaptation are compared respectively, and the strategies of first applying LR then MAP based on both MLE and DT criteria are evaluated. The effect of the amount of available data for adaptation is also compared in our experiments. The experiment results of 863 and Tsinghua mandarin evaluation tasks suggests that the process of first applying MWCE-LR then MWCE-MAP can achieve the best performance.
Year
DOI
Venue
2008
10.1109/CHINSL.2008.ECP.35
ISCSLP
Keywords
Field
DocType
minimum word classification error,discriminative training criteria,speech recognition,minimum word classification error criteria,regression analysis,maximum likelihood estimation,mwce-lr,index terms— adaptation,discriminative training,linear regression criteria,maximum a posteriori algorithm,mwce-map adaptation,mle,linear regression,estimation,measurement uncertainty,indexing terms,maximum likelihood estimate
Map adaptation,Pattern recognition,Regression analysis,Computer science,Maximum likelihood,Measurement uncertainty,Speech recognition,Artificial intelligence,Discriminative model,Mandarin Chinese,Maximum a posteriori algorithm,Linear regression
Conference
ISBN
Citations 
PageRank 
978-1-4244-2943-1
0
0.34
References 
Authors
9
6
Name
Order
Citations
PageRank
Bo Zhu100.34
Zhi-Jie Yan27714.34
Yu Hu353776.69
Zhiguo Wang4294.51
Li-Rong Dai51070117.92
Ren-Hua Wang634441.36