Entry Bang:2014:PVP from talip.bib
Last update: Sun Oct 15 02:55:04 MDT 2017
Top |
Symbols |
Numbers |
Math |
A |
B |
C |
D |
E |
F |
G |
H |
I |
J |
K |
L |
M |
N |
O |
P |
Q |
R |
S |
T |
U |
V |
W |
X |
Y |
Z
BibTeX entry
@Article{Bang:2014:PVP,
author = "Jeesoo Bang and Jonghoon Lee and Gary Geunbae Lee and
Minhwa Chung",
title = "Pronunciation Variants Prediction Method to Detect
Mispronunciations by {Korean} Learners of {English}",
journal = j-TALIP,
volume = "13",
number = "4",
pages = "16:1--16:??",
month = dec,
year = "2014",
CODEN = "????",
DOI = "https://doi.org/10.1145/2629545",
ISSN = "1530-0226 (print), 1558-3430 (electronic)",
ISSN-L = "1530-0226",
bibdate = "Wed Jan 7 15:23:49 MST 2015",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/talip.bib",
abstract = "This article presents an approach to nonnative
pronunciation variants modeling and prediction. The
pronunciation variants prediction method was developed
by generalized transformation-based error-driven
learning (GTBL). The modified goodness of pronunciation
(GOP) score was applied to effective mispronunciation
detection using logistic regression machine learning
under the pronunciation variants prediction.
English-read speech data uttered by Korean-speaking
learners of English were collected, then pronunciation
variation knowledge was extracted from the differences
between the canonical phonemes and the actual phonemes
of the speech data. With this knowledge, an
error-driven learning approach was designed that
automatically learns phoneme variation rules from
phoneme-level transcriptions. The learned rules
generate an extended recognition network to detect
mispronunciations. Three different mispronunciation
detection methods were tested including our logistic
regression machine learning method with modified GOP
scores and mispronunciation preference features; all
three methods yielded significant improvement in
predictions of pronunciation variants, and our logistic
regression method showed the best performance.",
acknowledgement = ack-nhfb,
articleno = "16",
fjournal = "ACM Transactions on Asian Language Information
Processing",
journal-URL = "http://portal.acm.org/browse_dl.cfm?idx=J820",
}
Related entries
- all,
6(4)2,
7(1)1,
7(2)7,
7(3)8,
7(4)11,
7(4)12,
8(2)7,
8(4)16,
8(4)17,
9(2)5,
9(3)11,
9(3)12,
10(2)9,
10(3)15,
11(2)6,
11(2)7,
11(4)18,
12(2)5,
12(3)9,
13(1)2,
13(2)6
- applied,
5(2)89,
5(2)121,
6(4)3,
8(4)19,
9(2)5,
9(3)11,
10(2)7,
13(1)4,
13(2)10,
13(3)12
- article,
3(4)227,
4(3)321,
5(2)121,
6(2)6,
6(2)7,
6(2)8,
6(4)3,
7(1)1,
7(1)3,
7(2)5,
7(2)6,
7(2)7,
7(3)8,
7(3)9,
7(4)11,
7(4)12,
7(4)13,
8(1)2,
8(1)3,
8(1)4,
8(2)6,
8(2)8,
8(2)9,
8(3)10,
8(3)11,
8(3)12,
8(4)14,
8(4)16,
8(4)17,
8(4)18,
9(1)2,
9(1)4,
9(2)6,
9(3)10,
9(3)11,
9(3)12,
9(4)13,
9(4)14,
10(1)3,
10(1)5,
10(1)6,
10(2)7,
10(2)9,
10(2)10,
10(3)12,
10(3)13,
10(3)14,
10(3)15,
10(4)17,
10(4)18,
10(4)20,
10(4)21,
11(1)1,
11(2)4,
11(2)5,
11(2)7,
11(3)8,
11(3)10,
11(3)11,
11(4)13,
11(4)14,
11(4)15,
11(4)16,
11(4)17,
11(4)18,
12(1)1,
12(1)3,
12(1)4,
12(2)5,
12(2)6,
12(2)7,
12(3)9,
12(3)10,
12(3)11,
12(3)12,
12(4)14,
13(1)1,
13(1)2,
13(1)3,
13(1)4,
13(2)6,
13(2)7,
13(2)8,
13(2)9,
13(3)12,
13(3)13
- automatically,
3(4)227,
5(2)89,
5(2)121,
5(2)165,
7(1)1,
7(2)6,
8(1)3,
8(2)7,
8(3)10,
9(2)6,
10(3)12,
11(2)6,
11(4)16,
12(2)7,
12(4)15,
13(3)12
- based, transformation-,
3(2)159
- best,
5(2)89,
5(3)183,
7(2)7,
7(4)13,
8(2)6,
9(1)3,
9(2)7,
9(3)11,
9(3)12,
11(3)8,
11(4)13,
12(1)2,
12(2)5,
12(2)7,
12(3)9,
12(4)14,
13(1)4
- collected,
8(1)2
- data,
2(2)143,
6(1)z,
6(1)z-1,
6(2)7,
6(3)11,
7(1)3,
7(3)9,
7(4)13,
8(1)3,
8(2)7,
8(3)10,
8(3)11,
8(3)12,
8(4)16,
8(4)18,
9(2)6,
10(2)7,
10(3)12,
10(4)20,
11(2)4,
11(3)10,
11(3)11,
11(4)13,
11(4)14,
11(4)18,
12(1)1,
12(2)7,
12(3)9,
13(1)2,
13(1)3,
13(1)4,
13(4)17,
13(4)18
- designed,
6(2)8,
6(3)9,
7(4)11,
7(4)12,
10(1)3
- detect,
10(4)21,
11(3)8
- detection,
2(2)85,
6(3)11,
7(3)10,
8(4)16,
8(4)17,
9(1)2,
10(1)5,
10(1)6,
10(4)20,
10(4)21,
11(4)17,
13(2)10
- developed,
7(2)7,
10(1)2,
10(1)4,
10(3)12,
11(1)2
- difference,
7(3)10,
8(4)18,
9(1)3,
9(2)5,
9(3)11,
10(1)2,
10(4)17,
12(1)1,
12(3)11,
13(2)10
- different,
5(2)89,
6(3)9,
6(4)3,
7(2)7,
7(3)8,
7(4)13,
8(1)2,
8(2)7,
8(2)8,
8(3)11,
8(4)16,
8(4)17,
9(1)1,
9(1)4,
9(2)5,
9(2)6,
9(3)12,
10(1)4,
10(1)5,
10(3)12,
10(4)17,
10(4)19,
11(3)8,
11(3)11,
11(4)16,
11(4)17,
11(4)18,
12(1)2,
12(3)11,
12(4)17,
13(2)6,
13(3)11
- effective,
4(2)78,
6(2)7,
6(3)11,
7(4)12,
7(4)13,
8(1)2,
8(3)10,
9(2)5,
9(3)12,
10(2)10,
10(3)14,
10(4)17,
10(4)18,
11(2)4,
11(2)7,
11(4)18,
12(2)7,
12(4)14,
13(3)13
- English,
2(3)245,
4(2)135,
5(2)89,
5(2)121,
5(3)245,
6(2)6,
6(2)7,
6(3)11,
6(4)2,
7(1)1,
7(4)11,
8(2)9,
8(4)15,
8(4)16,
8(4)17,
9(1)1,
9(1)3,
9(2)7,
9(3)12,
9(4)14,
9(4)15,
10(1)2,
10(1)4,
10(2)8,
10(3)14,
10(3)15,
10(4)17,
11(2)4,
11(2)5,
11(2)6,
11(3)8,
11(3)11,
12(2)5,
12(3)12,
12(4)14,
12(4)17,
13(1)1
- extended,
5(3)183,
7(3)10,
7(4)13,
8(4)15,
8(4)18,
9(1)3,
11(2)6
- extracted,
3(4)227,
4(3)321,
6(2)8,
7(1)1,
7(1)3,
8(3)10,
9(1)1,
11(2)6,
11(3)11,
13(2)9,
13(3)14
- feature,
2(3)290,
5(2)165,
6(4)1,
7(2)6,
7(2)7,
7(3)10,
7(4)13,
8(3)11,
8(4)14,
8(4)17,
9(1)2,
9(2)5,
9(2)6,
10(1)5,
10(1)6,
10(2)7,
10(3)13,
10(3)15,
10(4)17,
10(4)19,
10(4)21,
11(3)10,
11(4)14,
11(4)16,
12(1)1,
12(1)4,
12(3)9,
12(3)10,
13(2)9,
13(3)13
- generalized,
2(3)193,
9(1)3,
11(2)4
- generate,
3(3)190,
5(2)121,
7(3)10,
8(1)4,
10(3)16,
12(3)9,
12(4)15
- improvement,
4(3)280,
5(2)121,
6(2)7,
7(1)2,
7(1)3,
7(3)8,
7(3)10,
8(1)4,
8(3)10,
8(4)15,
8(4)16,
9(1)3,
9(3)11,
10(2)8,
11(4)17,
11(4)18,
12(1)1,
12(2)7,
12(3)11,
13(3)12,
13(3)14,
13(4)17
- including,
5(2)121,
6(2)7,
7(1)3,
7(2)7,
8(1)3,
8(2)6,
9(1)1,
9(2)7,
9(3)11,
10(3)12,
11(4)18
- knowledge,
4(4)435,
5(1)4,
5(1)74,
5(2)121,
5(2)146,
7(3)9,
7(4)12,
8(1)4,
9(1)3,
11(1)3,
11(2)4,
11(4)13,
11(4)15,
11(4)16,
11(4)17,
11(4)18
- Korean,
2(4)301,
2(4)324,
3(1)51,
4(2)135,
11(3)10,
13(1)3
- learn,
7(1)1,
9(1)3,
12(1)3,
13(1)2
- learned,
4(2)78,
13(4)17
- learners,
10(1)3,
11(1)3,
12(4)15
- learning,
3(2)159,
5(1)61,
5(2)121,
5(4)413,
6(2)6,
6(4)1,
6(4)3,
7(2)7,
7(3)9,
8(3)10,
8(4)15,
9(1)3,
9(2)5,
10(1)5,
10(2)10,
10(3)16,
10(4)20,
10(4)21,
11(1)3,
11(4)14,
11(4)16,
12(1)1,
12(1)3,
12(2)5,
12(2)7,
12(4)15,
13(1)2,
13(1)3,
13(2)9,
13(4)17
- Lee, Gary Geunbae,
1(1)65,
1(3)207,
5(1)1,
5(1)61,
7(1)2,
11(3)10,
13(1)3
- Lee, Jonghoon,
11(3)10,
13(1)3
- machine,
4(1)18,
4(4)377,
5(2)89,
5(3)185,
6(2)6,
6(4)2,
6(4)3,
7(1)1,
7(2)5,
7(2)7,
7(3)9,
7(3)10,
8(1)4,
8(2)5,
8(2)6,
8(2)7,
8(2)8,
8(2)9,
8(3)10,
8(4)15,
9(1)3,
9(4)13,
10(1)2,
10(1)5,
10(3)16,
10(4)18,
10(4)20,
11(1)2,
11(3)8,
11(4)14,
11(4)16,
12(3)9,
12(3)12,
12(4)14,
12(4)16,
12(4)17,
13(1)2,
13(3)11,
13(4)17
- modeling,
1(1)3,
1(3)173,
3(2)87,
3(3)169,
6(1)z,
6(2)6,
6(3)9,
7(3)10,
7(4)13,
8(1)2,
8(1)4,
9(4)14,
10(4)18,
10(4)21,
11(2)5,
12(2)5,
13(3)12
- network,
4(1)38,
7(3)10,
8(1)4,
11(4)15,
13(4)18
- performance,
5(2)121,
5(2)165,
6(2)8,
6(3)9,
6(4)1,
6(4)3,
7(1)1,
7(1)2,
7(2)5,
7(2)6,
7(2)7,
7(3)9,
7(3)10,
7(4)13,
8(1)2,
8(1)3,
8(2)7,
8(2)8,
8(2)9,
8(3)10,
8(4)16,
8(4)17,
8(4)18,
9(1)2,
9(1)4,
9(2)5,
9(2)6,
9(3)11,
9(3)12,
9(4)14,
10(2)8,
10(3)13,
10(3)14,
11(2)7,
11(3)10,
11(3)11,
11(4)14,
11(4)15,
11(4)17,
12(1)2,
12(3)9,
12(3)11,
12(4)14,
12(4)15,
12(4)16,
13(1)3,
13(1)4,
13(2)7,
13(2)9,
13(4)17
- phoneme,
1(1)65,
5(3)185
- prediction,
1(3)207,
10(2)9,
11(4)15,
12(4)15,
13(2)8
- preference,
11(2)4,
13(1)2
- present,
5(2)89,
5(2)165,
6(2)7,
6(3)10,
6(4)2,
7(1)2,
7(1)3,
7(2)7,
7(3)9,
7(4)11,
7(4)13,
8(1)3,
8(2)6,
8(2)7,
8(2)8,
8(3)10,
8(4)14,
8(4)16,
8(4)17,
8(4)18,
8(4)19,
9(1)1,
9(1)2,
9(1)3,
9(2)6,
9(4)14,
10(1)4,
10(1)6,
10(2)7,
10(3)14,
10(4)18,
10(4)19,
11(1)2,
11(1)3,
11(2)4,
11(2)5,
11(2)6,
11(3)10,
11(4)13,
12(1)3,
12(2)5,
12(3)9,
12(3)11,
12(4)15,
13(2)8
- pronunciation,
10(2)7
- recognition,
1(1)83,
1(4)297,
2(1)27,
2(3)290,
5(1)4,
5(2)165,
6(2)6,
6(3)9,
6(4)3,
7(1)2,
7(3)10,
8(1)2,
8(3)11,
8(4)18,
9(1)2,
9(2)7,
10(1)6,
10(2)7,
10(2)9,
10(3)13,
11(1)1,
11(1)2,
11(4)13,
11(4)16,
11(4)17,
11(4)18,
12(1)4,
12(3)10,
13(3)12
- rule,
5(2)165,
7(1)1,
7(4)12,
9(1)3,
9(4)14,
10(2)8,
11(1)3,
11(3)8,
11(4)15,
12(3)11
- score,
7(2)7,
7(4)12,
8(2)7,
8(3)10,
9(1)3,
9(2)6,
10(4)18,
11(2)6,
12(3)9,
12(4)17,
13(1)2,
13(3)13
- showed,
6(3)11,
7(3)8,
10(4)18,
11(3)9,
12(4)17,
13(2)6
- significant,
5(2)121,
7(1)3,
8(1)4,
8(4)15,
8(4)16,
8(4)17,
8(4)18,
9(2)5,
9(3)11,
10(1)5,
10(2)8,
10(3)14,
11(2)6,
11(2)7,
12(1)1,
12(4)16,
13(1)3,
13(3)14
- speech,
1(1)83,
4(1)38,
6(3)9,
7(1)2,
7(3)10,
8(1)2,
8(1)4,
8(4)14,
8(4)18,
9(1)2,
9(2)7,
10(1)6,
10(2)7,
11(1)2,
11(3)10
- tested,
6(3)11,
9(1)3,
11(2)7,
12(1)4,
13(2)6
- then,
5(2)121,
6(2)6,
7(1)1,
7(3)10,
7(4)12,
8(1)4,
8(2)7,
8(3)10,
8(3)11,
8(3)12,
8(4)14,
9(1)1,
9(2)7,
9(3)11,
10(2)7,
10(3)13,
10(4)20,
11(1)3,
11(2)7,
11(3)11,
11(4)15,
12(1)3,
12(3)10,
12(4)17,
13(1)4,
13(2)9,
13(3)13
- three,
1(2)145,
5(2)165,
7(2)7,
7(3)8,
8(1)4,
8(3)12,
9(2)5,
9(2)6,
9(3)11,
10(1)5,
10(4)18,
11(4)17,
13(3)11
- transcription,
2(1)63,
8(1)2,
8(1)4,
8(4)18
- transformation-based,
3(2)159
- variant,
7(4)11,
10(1)3,
10(2)8
- variation,
8(4)19,
9(1)3,
12(2)6,
12(4)14,
13(3)12
- was,
5(2)146,
6(3)9,
6(3)11,
8(4)18,
8(4)19,
9(2)7,
9(3)10,
10(4)18,
11(1)2,
11(3)10,
12(4)14,
13(1)4
- were,
6(3)9,
9(2)7,
10(1)2,
10(2)10,
11(3)10,
11(4)13,
12(4)17,
13(2)6
- yielded,
9(1)3