Study on a speech learning approach based on interval support vector regression

Author

Liu, Peipei

Author_Institution

Dept. of Comput., North China Electr. Power Univ., Baoding, China

fYear

2009

fDate

25-28 July 2009

Firstpage

1009

Lastpage

1012

Abstract

In this paper an interval regression model has been established to cope with the situation that the input training data is accurate while the output one is interval. And the model has been applied in English speech learning system to predict the credible interval of correct speech and then give a correct judgment for the learners. Experimental data show that the new model reduces the workload of fuzzy prediction and has good accuracy, so it can be effective in speech learning system.

Keywords

computer aided instruction; eigenvalues and eigenfunctions; fuzzy set theory; learning (artificial intelligence); linguistics; regression analysis; speech recognition; speech synthesis; support vector machines; CALL system; English speech learning system; computer-assisted language learning system; eigenvector extraction; fuzzy prediction; interval support vector regression model; speech recognition; speech synthesis; training data; Computer science; Computer science education; Learning systems; Linear regression; Power system modeling; Predictive models; Speech recognition; Support vector machine classification; Support vector machines; Training data; SVR; eigenvector extraction; interval regression; speech learning;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science & Education, 2009. ICCSE '09. 4th International Conference on

Conference_Location

Nanning

Print_ISBN

978-1-4244-3520-3

Electronic_ISBN

978-1-4244-3521-0

Type

conf

DOI

10.1109/ICCSE.2009.5228399

Filename

5228399