1. A Predictive Blissymbolic to English Translation System
Annalu Waller and Kris Jack
Department of Applied Computing
University of Dundee

2. Outline
Background
Method
Results
Discussion and Future Work

3. Background (1) Blissymbolics …
a semantic written language based on Semantography (C.K. Bliss, 1965)
first used for augmentative and alternative (AAC) in Canada in 1971
written language comprising characters and words...

4. Background (2) Gloss-to-Speech Translation
boy (to) go home
Translation: boy to go home

5. Background (3) Rule-Based Translation
boy (to) go home
Translation: boy goes home

6. Background (4) A solution? Stochastic Translation
boy (to) go home
Translation: The/A boy goes home
The/A boy is going home

7. Method Bliss Dictionary Source Text Files Bliss Translator
Word Association
Dictionary

8. Method Bliss Dictionary Source Text Files Bliss Translator
E.g. Gutenberg Texts
Word Association
Dictionary

9. Method Bliss Dictionary Source Text Files ISO Number Gloss(es)
Bitmap File
Bliss
Translator
Word Association
Dictionary

10. Method Bliss Dictionary Source Text Files Bliss Translator
Word Association
Dictionary
Words
Frequencies…

11. Method Word Association Dictionary
Start 24 6 2 .
the
boy 1 3
girl 13 a a . . 7 an .

12. Method Bliss Dictionary Source Text Files Bliss Translator
The Algorithm…
Word Association
Dictionary

13. Translation Algorithm Step 1:. Construct possible phrases using
Translation Algorithm Step 1: Construct possible phrases using tri-grams and gloss synonyms.
Example input:
A B C where each letter represents a Bliss word e.g. boy (to) go home

14. Translation Algorithm Step 1:. Construct possible phrases using
Translation Algorithm Step 1: Construct possible phrases using tri-grams and gloss synonyms.
Example input:
A B C where each letter represents a Bliss word e.g. boy (to) go home
A B C e.g. boy go home
A B1 C e.g. boy goes home
A B2 C e.g. boy going home

15. Translation Algorithm Step 1:. Construct possible phrases using
Translation Algorithm Step 1: Construct possible phrases using tri-grams and gloss synonyms.
Example input:
A B C where each letter represents a Bliss word e.g. boy (to) go home
A B C e.g. boy go home
A B1 C e.g. boy goes home
A B2 C e.g. boy going home
A D B C e.g. boy does go home

16. Translation Algorithm Step 1:. Construct possible phrases using
Translation Algorithm Step 1: Construct possible phrases using tri-grams and gloss synonyms.
Example input:
A B C where each letter represents a Bliss word e.g. boy (to) go home
A B C e.g. boy go home
A B1 C e.g. boy goes home
A B2 C e.g. boy going home
A D B C e.g. boy does go home
A B E C e.g. boy go to home

17. Translation Algorithm Step 1:. Construct possible phrases using
Translation Algorithm Step 1: Construct possible phrases using tri-grams and gloss synonyms.
Example input:
A B C where each letter represents a Bliss word e.g. boy (to) go home
A B C e.g. boy go home
A B1 C e.g. boy goes home
A B2 C e.g. boy going home
A D B C e.g. boy does go home
A B E C e.g. boy go to home
A D B E C e.g. boy will go at home

18. Translation Algorithm Step 2: Find probability of phrases
P(B, A) = frequency of B / frequency of A
P(C, AB) = frequency of C / frequency of A
P(D, ABC) = frequency of D / frequency of A
Repeat process until all Bliss words have been used
Include period at the beginning of each translation

19. Results Time taken to build a word association dictionary
Accuracy of translation
Time taken to translate a sentence

20. Accuracy of Translation (1)
Gloss Sequence
50,000 Word Source 1
boy
Boy 2
(to) run
Run 3
green
Green 4 no No 5
I/me + (to) walk
I walks 6
us + (to) eat
when we eat 7
JOHN + (to) play
john play 8
that + right
all that right 9
I/me + (to) want + (to) see
I wants sees 10
my + picture + best
my picture best 11
I/me + (to) go + bed
I goes bed 12
what? + his + name
what his name 13
I/me + (to) want + (to) go + zoo
I wants goes zoo 14
(to) meet + me + at + cabin
meet I at cabin 15
I/me + (to) like + (to) eat + cake
I likes eats cake 16
my + favourite + colour + orange
my favourite colour orange 17
(to) push + chair + on + far + right
push chair on far right 18
I/me + not + enough + time + today
when I have not enough time today 19
girl + (to) laugh + when + he/she + (to) play
girl laugh when he plays 20
my + brother + outside + (to) wait + I/me
my brother outside waiting I

21. Accuracy of Translation (2)
Gloss Sequence
1,000,000 Word Source 1
boy
the boy 2
(to) run
Run 3
green
Green 4 no No 5
I/me + (to) walk
and I walks 6
us + (to) eat
if we eat 7
JOHN + (to) play
King john play 8
that + right
that the right 9
I/me + (to) want + (to) see
and I wants sees 10
my + picture + best
at my picture best 11
I/me + (to) go + bed
I am going to bed 12
what? + his + name
do what her own name 13
I/me + (to) want + (to) go + zoo
and I wants goes zoo 14
(to) meet + me + at + cabin
the meeting I must at cabin 15
I/me + (to) like + (to) eat + cake
and I likes eat cake 16
my + favourite + colour + orange
my favourite colour orange 17
(to) push + chair + on + far + right
push chair on with far right 18
I/me + not + enough + time + today
I know not force enough time today 19
girl + (to) laugh + when + he/she + (to) play
the girl laugh when she plays 20
my + brother + outside + (to) wait + I/me
my brother outside waits I

22. Accuracy of Translation (3)
Gloss Sequence
10,000,000 Word Source 1
boy
the boy 2
(to) run
Run 3
green
Green 4 no No 5
I/me + (to) walk
I am walking 6
us + (to) eat
we eat 7
JOHN + (to) play
this john play 8
that + right
that right 9
I/me + (to) want + (to) see
I want to see 10
my + picture + best
in my picture best 11
I/me + (to) go + bed
I am going to bed 12
what? + his + name
What is his name 13
I/me + (to) want + (to) go + zoo
I want going zoo 14
(to) meet + me + at + cabin
they meet me at the cabin 15
I/me + (to) like + (to) eat + cake
I like eating cake 16
my + favourite + colour + orange
my favourite colour orange 17
(to) push + chair + on + far + right
her push chair on as far right 18
I/me + not + enough + time + today
I am not good enough time today 19
girl + (to) laugh + when + he/she + (to) play
this girl laugh when suddenly she plays 20
my + brother + outside + (to) wait + I/me
my brother outside is waiting I

23. Accuracy of Translation (4)
50,000 Word Source
1,000,000 Word Source
10,000,000 Word Source
Correct 4 5 11
Incorrect
No Confidence 12

24. Time taken to translate a sentence

25. Discussion & Future work
Stochastic method has possibilities
Improvements to algorithm using Bliss semantic information
Integration of user interface
Development of Bliss font