DocumentCode :
114031
Title :
Structure-based prediction of English pronunciation distances and its analytical investigation
Author :
Kasahara, Shun ; Minematsu, Nobuaki ; HanPing Shen ; Saito, Daisuke ; Hirose, Keikichi
Author_Institution :
Grad. Sch. of Eng., Univ. of Tokyo, Tokyo, Japan
fYear :
2014
fDate :
26-28 April 2014
Firstpage :
332
Lastpage :
336
Abstract :
English is the only language available for international communication and is used by approximately 1.5 billions of speakers. It is also known to have a large diversity of pronunciation partly due to the influence of the speakers´ mother tongue, called accents. Our project aims at creating a global and individual-basis map of English pronunciations to be used in teaching and learning World Englishes (WE) as well as research studies of WE [1], [2]. Creating the map mathematically requires a distance matrix in terms of pronunciation differences among all the speakers considered, and technically requires a method of predicting the pronunciation distance between any pair of the speakers. Our previous but very recent study [3] combined invariant pronunciation structure analysis [4], [5], [6], [7] and Support Vector Regression (SVR) effectively to predict the interspeaker pronunciation distances. In [3], very high correlation of 0.903 was observed between reference IPA-based pronunciation distances and the distances predicted by our proposed method. In this paper, after explaining our proposed method, some new results of analytical investigation of the method are described.
Keywords :
matrix algebra; regression analysis; speaker recognition; support vector machines; English pronunciation distance; IPA-based pronunciation distance; WE; World English learning; World English teaching; distance matrix; interspeaker pronunciation distance; invariant pronunciation structure analysis; pronunciation difference; structure-based prediction; support vector regression; Acoustics; Correlation; Educational institutions; Electronic mail; Hidden Markov models; Speech; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Technology (ICIST), 2014 4th IEEE International Conference on
Conference_Location :
Shenzhen
Type :
conf
DOI :
10.1109/ICIST.2014.6920396
Filename :
6920396
Link To Document :
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