3. Education
• Japanese Literature (Classic/Modern)
Meiji University (80–84)
• SLA training and research
National Institute of Japanese Language (87–88)
• Educational Technology
Graduate School, Naruto University of Education (89–92)
• Corpus Linguistics / Vocabulary
Australian National University (03–06)
3
4. Research
• Study of Japanese vocabulary
– Vocabulary dominates all language skills!
– How to teach vocabulary efficiently!
• Teaching Japanese for Specific Purpose (JSP)
– MIT summer course for Technical Japanese
– CALL, CMI, e-Learning, SPOT
– DVD and video clip development (copyleft/licence free)
• Corpus/Mathematical Linguistics
– Language Modelling of the meaning of words
– Study of connotation
– The Kokinsh¯ and Hachidaish¯ database
u u
4
5. The Study of Connotation
An introduction to the Computer Modelling of Vocabulary
5
6. What is connotation?
Connotations are the individual feelings we have about words, (and) the
associations they arouse in our minds. (Crystal 1984, 18)
→ Can we describe connotation?
Octopus
It may be that connotations are particularly difficult to retrieve reliably by
intuition because they are not directly observable in individual texts, but
depend on intertextual norm. (Stubbs, 2001; 198)
6
7. What is connotation?
Connotations are the individual feelings we have about words, (and) the
associations they arouse in our minds. (Crystal 1984, 18)
→ Can we describe connotation?
Octopus
weird
spooky ...
It may be that connotations are particularly difficult to retrieve reliably by
intuition because they are not directly observable in individual texts, but
depend on intertextual norm. (Stubbs, 2001; 198)
6-a
8. What is connotation?
Connotations are the individual feelings we have about words, (and) the
associations they arouse in our minds. (Crystal 1984, 18)
→ Can we describe connotation?
Octopus
weird takoyaki
spooky ... (fried octopus!)
= delicious
It may be that connotations are particularly difficult to retrieve reliably by
intuition because they are not directly observable in individual texts, but
depend on intertextual norm. (Stubbs, 2001; 198)
6-b
9. What is connotation?
Connotations are the individual feelings we have about words, (and) the
associations they arouse in our minds. (Crystal 1984, 18)
→ Can we describe connotation?
‘Connotation’ depends on the receiver of a message.
Octopus
weird takoyaki
spooky ... (fried octopus!)
= delicious
It may be that connotations are particularly difficult to retrieve reliably by
intuition because they are not directly observable in individual texts, but
depend on intertextual norm. (Stubbs, 2001; 198)
6-c
10. What is connotation?
Connotations are the individual feelings we have about words, (and) the
associations they arouse in our minds. (Crystal 1984, 18)
→ Can we describe connotation?
‘Connotation’ depends on the receiver of a message.
Octopus
weird takoyaki
spooky ... (fried octopus!)
= delicious
It may be that connotations are particularly difficult to retrieve reliably by
intuition because they are not directly observable in individual texts, but
depend on intertextual norm. (Stubbs, 2001; 198)
6-d
11. Material
• the Kokinsh¯ (ca. 905) (1,111 poems) (OP)
u
• Ten sets of contemporary Japanese translation of the Kokinsh¯
u
(CT)
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12. 10th century 20th century
Field of experience Field of experience (expert)
poet write OP read expert reader
com
par write
e
CT
read
novice reader
20th century
Field of experience
(novice)
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13. Alignment of OP and CT
OP...original poems
CT...contemporary translations
CT ( ) ( )
OP ——— — — — — — — — — ————— —
CT ( ) ( ) ( ) ( )
OP — — [ ] —— — —— —
CT298 translated by Teruhiko Komachiya (Komachiya 1982)
9
14. How to Build Models
• Use OP and 10 sets of CT (1,000 OP + 10,000 CT)
• Sentences are tokenised and transformed into words.
• Generate co-occurrence patterns which are:
→ combinations of any two words appearing in a text (a poem).
• Visualisation by Graph Theory
10
15. Example of Co-occurrence pattern
yuki no uchi ni haru wa ki ni keri uguisu no
snow of inside at spring (topic) come (past) (perfect) warbler of
Patterns may number up to 5,000.
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16. Visualisation by graph theory
→ an example of a simple graph
reality abstraction
→ John
hit
Mary
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18. clearly
around smell.vt.1
moonless night 7
5 4
5
go over 8
Kurabu.PN 7
dark
8 light green
13
twist
white dew penetrate
within the year
6
9 5
plum 4 blend
last year 6 8 7
7
11 5 thread
8
green willow tousle
13
this year 61 bloom.n 10
willow brocade.1
snow 7
34 137 24 10
6
89
24 green
gem
confine
spring look over
4
88
show
5
9 62
5
steal
bud warbler
mountain breeze 6
7 17 6
8 7
weft mist tranquil
30 14
Model of Spring 10
10
hide.vt
stand.vi 12
36
10
trail
30
10
Tatsuta.PN 50 28
cherry
31
31
mountain 64
9
swing
illuminate spring haze 11
envelop
18
go out burn 9 27
7
7
7 27
field guardian 9
Kasuga.PN
5 rare
5 6 goose
rise
5 31
how many days 5 7
Kasugano.PN 10
5 7 9 go back
4 5 14
cloud.vi sun
Tobuhino.PN
5 10 north
can pick 16
23 sky 7
8 come out 9
9 7
18
country
42
pick Mikasa.PN
young herb
6
fall 10 3
10 16 10
47 19
far away
bright yellow 10
7 spring rain
10 tomorrow
field moon
look up 14
wash 23
7
drench 10
heat haze
stretch
19. hand
mountain
10
spring haze
10
touch 9
hide.vi.2
6 stop.vi.1 Tatsuta.PN 10
sing.vi stand.vi
10
sew.2 7 10
flowerbranch 15
145 yet.1
10
4 138 30
6 35
52
scatter.1
23
4
wear in (my) hair woven hat
10
10
plum 56
warbler 88
4
62 spring
29
green willow 6
22
voice
17 9
cry.vi 10
break off
fragrance.1
old age field
lure 7
8
every morning
4
4 send
5
6
guidance.1 15
near attach
warbler (23/229,3.73): CT cw.>15;
non-dist=off; idf=on(2)
23. force
hand 6
mountain cuckoo
old age
green willow 10
summer mountains 9
side
8
wear in (my) hair
4
6 midsummer rain singing voice 8
4 4 touch hear
11
be heard.1 summer
14
21 10 a cry
sew.2 69
6 woven hat branch spring 37 39 12
borrow
6 7 10 23
10 19
hide.vi.2 plum cry.vi
10
35
stop.vi.1
15
88
voice 174
cuckoo 20
last year
29 10 6
56
261 42 20
29
62 110
flower 138 warbler 145 sing.vi 26
44 May
20
this morning flutter.2
6
treetop
10 9
17
8 field
22 30 10
mountain 19
11
9
10
6 every morning 10
9
52 20
near 9 yet.1 Otowa.PN
7 go over
10
break off Tatsuta.PN 8
5 imperceptibly
10
scatter.1
7
lure 4 10 7
iris.1 far
guidance.1 4 reason.1 6
9 10
4
treetop high.1
7
5
7 treetop high.3
regretseparation
send
spring haze
stand.vi
attach
19
fragrance.1
warbler-CT-23-229-3.73-15 cuckoo-CT-40-370-3.27-16
24. Conclusion
• We can see the non-literal aspect of a word meaning through
visualisation.
• Graph models include fractal shapes.
• Co-occurrence pattern can indicate contextual information.
• Even if two objects seem similar, their meanings in poetry are very
different.
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25. Language Teaching for Wollongong Students
• Motivation
1. “What a fantastic language Japanese is!”
2. “How cool learning Japanese is!”
• Learning other than Japanese using Japanese as a tool.
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26. Japanese is special/fantastic!
1. Independent from other language family.
2. The Sixth place of the most spoken language.
3. Spoken by over one million people.
4. The language form has not been largely changed since 1,000 years
ago.
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27. You can see Japanese everywhere!
• SUBARU
Hoshi wa SUBARU. (A star is SUBARU.)
→ SUBARU is the most beautiful star.
• CAMRY
a car name “TOYOTA CAMRY” but also “kanmuri” (crown)
→ Both are classical words.
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28. My Contribution to the students’ learning
1. Keep students motivated/exciting.
e.g. using authentic materials such as film, music, anime, manga etc.
also computer assisted material/curriculum design.. + good assessment
2. Invite guest speakers/lectures from Japan
to write some project grant applications.
3. Send students to Japan
to promote exchange program
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