Phonology
description
Transcript of Phonology
600.465 - Intro to NLP - J. Eisner 1
Phonology
[These slides are missing most examples and discussion from class …]
600.465 - Intro to NLP - J. Eisner 2
“kats” “dawgz”“roziz”“kisiz”
Pronunciation
What is Phonology?
cat + -s dog + -s rose + -s kiss + -s
cats dogsroseskisses
Spelling
How do you pronounce a sequence of morphemes?
Especially, how & why do you fix up the pronunciation at the seams between morphemes?
why?
phonology doesn’t care about the spelling (that’s just applied
morphology)
600.465 - Intro to NLP - J. Eisner 3
“næpt” “næbd”“nadid”“natid”
Pronunciation
What is Phonology?
nap + -t nab + -t nod + -t knot + -t
napped nabbednoddedknotted
Spelling
Actually, these are pronounced identically:
na∂Idthanks to the English “flapping” rule
(similarly: ladder/latter, bedding/betting)
600.465 - Intro to NLP - J. Eisner 4
“Trisyllabic Shortening” in English
What is Phonology?
divine divinityfutile futilitysenile senilitysatire satiricaldecide decisionwild wilderness
serene serenitysupreme supremityobscene obscenityobese *obesity
(and similarly for other vowels)
600.465 - Intro to NLP - J. Eisner 5
What is Phonology?
A function twixt head and lip
What class of functions is allowed?
Differs from one language to next Often complicated, but not arbitrary
Comp Sci: How to compute, invert, learn?
Morphology(head)
Phonologicalmapping
Articulation(mouth)
underlyingphonemes
surfacephones
ree-ZIYNreh-zihg-NAY-shun
resignresign + -ation
600.465 - Intro to NLP - J. Eisner 6
Successive Fixups for Phonology
Chomsky & Halle (1968) Stepwise refinement of a single form How to handle “resignation” example?
That is, O = f(I) = g3(g2(g1(I))) Function composition (e.g., transducer composition)
Rule 1
Rule 2input (I)
output (O)Rule
3
600.465 - Intro to NLP - J. Eisner 7
How to Give Orders
Directions version: Break two eggs into a medium mixing bowl. Remove this tab first. On the last day of each month, come to this office
and pay your rent. Rules version:
No running in the house is allowed. All dogs must be on a leash. Rent must be paid by the first day of each month.
In rules version, describe what a good solution would look like, plus a search procedure for finding the best solution). Where else have we seen this?
successive fixup (derivation)
successive winnowing (optimization)
example courtesy of K. Crosswhite
600.465 - Intro to NLP - J. Eisner 8
Optimality Theoryfor Phonology
Prince & Smolensky (1993) Alternative to successive
fixups Successive winnowing of candidate
setGen
Constr
aint 1
Constr
aint 2
Constr
aint 3
input
. . .
output
600.465 - Intro to NLP - J. Eisner 9
Optimality Theory “Tableau”
Constraint 1 Constraint 2 Constraint 3 Constraint 4
Candidate A Candidate B Candidate C Candidate D Candidate E Candidate F
constraint would prefer A, but onlyallowed to break tie among B,D,E
= candidate violates constraint twice (weight 2)
600.465 - Intro to NLP - J. Eisner 10
Optimality Theoryfor Phonology
Gen
Constr
aint 1
Constr
aint 2
Constr
aint 3
input (I)
. . .
output (O)
adds
wei
ghts
to can
dida
tes
adds
wei
ghts
to can
dida
tes
best
pat
hs (s
ever
al m
ay ti
e)
best
pat
hs (b
reak
s so
me
ties)
600.465 - Intro to NLP - J. Eisner 11
When do we prune back to best paths?
Optimality Theory: At each intermediate stage
Noisy channel: After adding up all weights
. . .
output (O)
600.465 - Intro to NLP - J. Eisner 12
Why does order matter?
Optimality Theory: Each machine (FSA) can choose only among outputs that previous machines liked best
Noisy channel: Each machine (FST) alters the output produced by previous machines
. . .
output (O)
600.465 - Intro to NLP - J. Eisner 13
Final Remark on OT
Repeated best-paths only works for a single input
Better to build full FST for I O (invertible)Can do this e.g. if every constraint is
binary:Assigns each candidate either 1 star (“bad”) or
0 stars (“good”)Gen
Constr
aint 1
Constr
aint 2
Constr
aint 3
input (I)
. . .
output (O)
600.465 - Intro to NLP - J. Eisner 14
Optimality Theory “Tableau”
Constraint 1 Constraint 2 Constraint 3 Constraint 4
Candidate A Candidate B Candidate C Candidate D Candidate E Candidate F
all surviving candidates violate constraint 3, so we can’t eliminate any