Finnish OT Prosody

1. Finnish OT Prosody Lauri Karttunen CLS-41 April 7, 2005

2. Overview • Success of Finite-State Morphology • Lexical transducers • Two ways of describing morphological alterations • Sequential (Chomsky & Halle 1968) • Parallel (Koskenniemi 1983) • Finnish OT Prosody • Basic Facts • Finite-state implementation of Kiparsky’s 2003 analysis • with the FST tool (Beesley & Karttunen 2003) • Conclusion • Final thoughts

3. Analysis Generation hang V Past leaf N Pl leave N Pl leave V Sg3 leaves hanged hung Computational morphology

4. Two challenges • Morphotactics • Words are composed of smaller elements that must be combined in a certain order: • piti-less-ness is English • piti-ness-less is not English • Phonological alternations • The shape of an element may vary depending on the context • pity is realized as pitiin pitilessness • die becomes dy in dying

5. Morphology is regular (=rational) • The relation between the surface forms of a language and the corresponding lexical forms can be described as a regular relation. • A regular relation consists of ordered pairs of strings. • leaf+N+Pl : leaves hang+V+Past : hung • Any finite collection of such pairs is a regular relation. • Regular relations are closed under operations such as concatenation, iteration, union, and composition. • Complex regular relations can be derived from simple relations.

6. Morphology is finite-state • A regular relation can be defined using the metalanguage of regular expressions. • [{talk}|{walk}|{work}] [% +Base:0 | %+SgGen3:s| %+Progr:{ing}| %+Past:{ed}]; • A regular expression can be compiled into a finite-state transducer that implements the relation computationally.

7. Generation work+3rdSg --> works +Base:e +3rdSg:s a:a t:t +Progr:i e:n e:g a:a l:l k:k w:w o:o r:r +Past:e e:d

8. Analysis +Base:e +3rdSg:s a:a t:t +Progr:i e:n e:g a:a l:l k:k w:w o:o r:r +Past:e e:d talked --> talk+Past

9. vouloir +IndP +SG + P3 Finite-state transducer veut citation form inflection codes v o u l o i r +IndP +SG +P3 v e u t inflected form Lexical transducer • Bidirectional: generation or analysis • Compact and fast • Comprehensive systems have been built for over 40 languages: • English, German, Dutch, French, Italian, Spanish, Portuguese, Finnish, Russian, Turkish, Japanese, Korean, Basque, Greek, Arabic, Hebrew, Bulgarian, …

10. Morphotactics Lexicon Regular Expression Lexicon FST Lexical Transducer (a single FST) Compiler composition Rules Regular Expressions Rule FSTs Alternations f a t +Adj +Comp t e f a t r How lexical transducers are made

11. Koskenniemi 1983 Chomsky&Halle 1968 Lexical form Lexical form rule 1 rule 1 ... rule 2 rule 1 rule n Intermediate form Surface form intersect ... FST rule n Surface form Two-level rules vs. rewrite rules compose

12. Rewrite rules • ? u: ty ? A s • ? u: t I y ? A s • ? u: t u y ? a s • ? o:t u y ? a s Epenthesis Harmony Yawelmani Vowel Harmony Kisseberth 1969 Lowering

13. Two-level constraints ? u: t y ? A s ? o: t u y ? a s Epenthesis: Insert u or i (underspecification) Harmony: Rounding next to a round V of the same height. Lowering: Long u always realized as long o. Underlying representation controls all three alternations.

14. Rewrite Rules vs. Constraints • Two different ways of decomposing the complex relation between lexical and surface forms into a set of simpler relations that can be more easily understood and manipulated. • One approach may be more convenient than the other for particular applications.

15. Two-level model vs. OT • In some respects, the two-level model of Koskenniemi (1983) was ten years ahead of its time: • Symbol-to-symbol constraints, not string relations like rewrite rules. • Rules can refer to both input and output contexts. • Constraints on the output can be expressed directly. • Concepts such as FAITHFULNESS can be expressed straight-forwardly. • But two-level constraints were not violable and not ranked. All the constraints have to be satisfied to get any output.

16. Overview • Success of Finite-State Morphology • Two strains • Sequential (Chomsky & Halle 1968) • Parallel (Koskenniemi 1983) • Finnish OT Prosody • Basic Facts • Finite-state implementation of Kiparsky’s 2003 analysis • with the FST tool (Beesley & Karttunen 2003) • Conclusion • Final thoughts

17. Finnish Prosody: basic facts • The nucleus of a Finnish syllable must consist of a short vowel, a long vowel, or a diphthong. • Main stress is always on the first syllable, secondary stress occurs on non-initial syllables. • Adjacent syllables are never stressed. • Stressed syllable is initial in the foot. • ilmoittautuminen ‘registering’ (Nom Sg) • (íl.moit).(tàu.tu).(mì.nen)

18. Ternary feet in Finnish • Stress that would fall on a light syllable shifts on the following heavy syllable creating a ternary foot. • (ká.las).te.(lèm.me) ‘we are fishing’ • (íl.moit).(tàu.tu).mi.(sès.ta) ‘registering’ (Ela Sg) • (rá.kas).ta.(jàt.ta).ri.(àn.sa) ‘his mistresses’ (Par Pl) • Can we get these facts to come out “for free”, from the interaction of independently motivated principles? • Yes! • Paul Kiparsky “Finnish Noun Inflection” Generative Approaches to Finnic and Saami Linguistics, Diane Nelson and Satu Manninen (eds.), pp.109-161, CSLI Publications, 2003. • Nine Elenbaas and René Kager. "Ternary rhythm and the lapse constraint". Phonology 16. 273-329.

19. Non-OT and OT solutions • It is possible to define a cascade of replace rules that produce the desired result. • http://www.stanford.edu/~laurik/fsmbook/examples/FinnishProsody.html • But, following Kiparsky, we are going to do OT today, and in a more elegant way than is shown at • http://www.stanford.edu/~laurik/fsmbook/examples/FinnishOTProsody.html

20. Input language Compose the input language with GEN to produce a mapping from each input form to all of its output candidates .o. GEN Eliminate suboptimal candidates by applying constraints in the ranked order. At least one output candidate always survives. Constraint 1 Constraint 2 General Strategy By what finite-state operation?

21. Lenient Composition .O. • Let R be a relation that maps each input string to one or more outputs. • Let C be a constraint that eliminates some outputs. • R .O. Cis the relation that maps each input string that can meet the constraintC to the outputs that meet C and leaves the rest of the relation R unchanged. (Karttunen 1998) • Is constraint ranking rule ordering in disguise?

22. ka.la ka.lá ka.là ka.(là) ka.(lá) ká.la ká.lá ká.là ká.(là) ká.(lá) kà.la (kà.la) (ká).la (ká).lá (ká).là (ká).(là) (ká).(lá) (ká.là) (ká.lá) (ká.la) ☜ (ka.là) (ka.lá) Need a prolific GEN kà.lá kà.là kà.(là) kà.(lá) (kà).la (kà).lá (kà).là (kà).(là) (kà).(lá) (kà.là) (kà.lá) kala ‘fish’ (Nom Sg) 33 candidates

23. Basic definitions 1 • Using Parc/XRCE regular expression syntax: • define C [b | c | d | f | g | h | j | k | l | m | • n | p | q | r | s | t | v | w | x | z]; # Consonant • define HighV [u | y | i]; # High vowel • define MidV [e | o | ö]; # Mid vowel • define LowV [a | ä] ; # Low vowel • define USV [HighV | MidV | LowV]; # Unstressed Vowel • define MSV [á | é | í | ó | ú | ý | ä’ | ö’]; • define SSV [à | è | ì | ò | ù | y` | ä` | ö`]; • define SV [MSV | SSV]; # Stressed vowel • define V [USV | SV] ; # Vowel

24. Basic definitions 2 • define P [V | C]; # Phone • define B [[\P+] | .#.]; # Boundary • define E .#. | "."; # Edge • define Light [C* V]; # Light syllable • define Heavy [Light P+]; # Heavy syllable • define S [Heavy | Light]; # Syllable • define SS [S & $SV]; # Stressed syllable • define US [S & ~$SV]; # Unstressed syllable • define MSS [S & $MSV] ; # Syllable with main stress

25. GEN 1 • define MarkNonDiphthong [ [. .] -> "." || [HighV|MidV] _ LowV, • LowV _ MidV , • i _ [MidV - e], • u _ [MidV - o], • y _ [MidV - ö] ]; • Insert a syllable boundary between vowels that cannot form • a diphtong: i.a, e.a, a.e, i.o, u.e, y.e, etc. • define Syllabify C* V+ C* @-> ... "." || _ C V ; • Insert a syllable boundary after a maximal C* V+ C* pattern that is followed by C V. For example, strukturalismi -> struk.tu.ra.lis.mi.

26. GEN 2 • define Stress a (->) á|à, e (->) é|è, i (->) í|ì, • o (->) ó|ò, u (->) ú|ù, y (->) "y´"|"y`", • ä (->) "ä´"|"ä`", ö (->) "ö´"|"ö`"; • Optionally stress any vowel with a primary or secondary stress. • define Scan [[S ("." S ("." S)) & $SS] (->) "(" ... ")" || E _ E] ; • Optionally group syllables into unary, binary, or ternary feet when there is at least one stressed syllable. • define Gen [MarkNonDiphthongs .o. Syllabify .o. • Stress .o. Scan];

27. Demo! • regex {kala} .o. Gen (compose) • print lower-words (show output candidates) • print size (count them)

28. Kiparsky's nine constraints • Clash • AlignLeft • MainStress • FootBin • Lapse • NonFinal • StressToWeight • Parse • AllFeetFirst

29. Counting constraint violations • We use asterisks to mark constraint violations. We need a way to prefer candidates with the least number of violation marks. • define Viol ${*}; • define Viol0 ~Viol; # No violations • define Viol1 ~[Viol^2]; # At most one violation • define Viol2 ~[Viol^3]; # At most two violations • define Viol3 ~[Viol^4]; • This eliminates the violation marks after the candidate set has been pruned by a constraint. • define Pardon {*} -> 0;

30. Defining OT Constraints • Three types: • Unviolable constraints • Primary stress in Finnish • Ordinary violable constraints • Lapse • Gradient alignment constraints • All-Feet-First • Strategy: • We define an evaluation template for each of the three types and then define the individual constraints with the help of the templates.

31. Evaluation Template for Unviolable Constraints • define Unviolable(Candidates, Constraint) [ • Candidates • .o. • Constraint ]; • Example: • define MainStress(X) Unviolable(X, B MSS ~$MSS); • # B is the left edge of the word or "(". • # MSS is a syllable with a primary stress.

32. Evaluation Template for Ordinary Constraints • define Eval(Candidates, Violation, Left, Right) [ • Candidates • .o. • Violation -> ... {*} || Left _ Right • .O. • Viol3 .O. Viol2 .O. Viol1 .O. Viol0 • .o. • Pardon ]; • where Viol0 is ~${*}, Viol2 is ~[[${*}]^2], etc. and • Pardon is {*} -> 0 deleting all violation marks.

33. Evaluation Template for Left-Oriented Gradient Alignment • define EvalGradientLeft(Candidates, Violation, Left, Right) [ • Candidates .o. • Violation -> {*} ... || .#. Left _ Right • .o. • Violation -> {*}^2 ... || .#. Left^2 _ Right • .o. • Violation -> {*}^3... || .#. Left^3 _ Right • .o. • Violation -> {*}^4 ... || .#. Left^4 _ Right • .o. • Violation -> {*}^5 ... || .#. Left^5 _ Right • .o. • Violation -> {*}^6 ... || .#. Left^6 _ Right • .o. • Violation -> {*}^7 ... || .#. Left^7 _ Right • .o. • Violation -> {*}^8 ... || .#. Left^8 _ Right • .O. • Viol12 .O. Viol11 .O. Viol10 .O. Viol9 .O. Viol8 .O. Viol7 .O. • Viol6 .O. Viol5 .O. Viol4 .O. Viol3 .O. Viol2 .O. Viol1 .O. • Viol0 .o. Pardon ];

34. Clash, AlignLeft, MainStress • Clash • No stress on adjacent syllables. • define Clash(X) Eval(X, SS, SS B, ?*); • Align-Left • The stressed syllable is initial in the foot. • define AlignLeft(X) Eval(X, SV, .#. ~[?* "(" C*], ?*); • Main Stress • The primary stress in Finnish is on the first syllable. • define MainStress(X) Unviolable(X, B MSS ~$MSS);

35. FootBin, Lapse, NonFinal • Foot-Bin • Feet are minimally bimoraic and maximally bisyllabic. • define FootBin(X) Eval(X, "(” Light ") "|” ("S["." S]^>1, • ?* ,?*); • Lapse • Every unstressed syllable must be adjacent to a stressed syllable or to the word edge. • define Lapse(X) Eval(X, US, [B US B], [B US B]); • Non-Final • The final syllable is not stressed. • define NonFinal(X) Eval(X, SS, ?*, ~$S .#.);

36. StressToWeight, Parse, AllFeetFirst • Stress-To-Weight • Stressed syllables are heavy. • define StressToWeight(X) Eval(X, SS & Light, ?*, ")"| E); • License-s • Syllables are parsed into feet. • define Parse(X) Eval(X, S, E, E); • All-Ft-Left • The left edge of every foot coincides with the left edge of some prosodic word. • define AllFeetFirst(X) [ • EvalGradientLeft(X, "(", ~$"." "." ~$".", ?*) ];

37. Finnish Prosody • Kiparsky 2003: • define FinnishProsody(Input) [ • AllFeetFirst( Parse( StressToWeight( • NonFinal( Lapse( FootBin( MainStress( • AlignLeft( Clash( Input .o. Gen)))))))))];

38. FinnWords • regex FinnishProsody( {kalastelet} | {kalasteleminen} | • {ilmoittautuminen} | {järjestelmättömyydestänsä} | • {kalastelemme} | {ilmoittautumisesta} | • {järjestelmällisyydelläni} | {järjestelmällistämätöntä} | • {voimisteluttelemasta} | {opiskelija} | {opettamassa} | • {kalastelet} | {strukturalismi} | {onnittelemanikin} | • {mäki} | {perijä} | {repeämä} | {ergonomia} | • {puhelimellani} | {matematiikka} | {puhelimistani} | • {rakastajattariansa} | {kuningas} | {kainostelijat} | • {ravintolat} | {merkonomin} ) ; • Demo!

39. (ér.go).(nò.mi).a (íl.moit).(tàu.tu).mi.(sès.ta) (íl.moit).(tàu.tu).(mì.nen) (ón.nit).(tè.le).(mà.ni).kin (ó.pis).(kè.li).ja (ó.pet).ta.(màs.sa) (vói.mis).te.(lùt.te).le.(màs.ta) (strúk.tu).ra.(lìs.mi) (rá.vin).(tò.lat) (rá.kas).ta.(jàt.ta).ri.(àn.sa) (ré.pe).(ä`.mä) (pé.ri).jä (pú.he).li.(mèl.la).ni (pú.he).li.(mìs.ta).ni (mä’.ki) (má.te).ma.(tìik.ka) (mér.ko).(nò.min) (kái.nos).(tè.li).jat (ká.las).te.(lèm.me) (ká.las).te.(lè.mi).nen (ká.las).(tè.let) (kú.nin).gas (jä’r.jes).tel.(mä`l.li).syy.(dèl.lä).ni (jä’r.jes).(tèl.mät).tö.(my`y.des).(tä`n.sä) (jä’r.jes).(tèl.mäl).(lìs.tä).mä.(tö`n.tä) Result

40. Two Errors • (ká.las).te.(lè.mi).nen • (jä´r.jes).tel.(mä`l.li).syy.(dèl.lä).ni • The interaction of Lapse and StressToWeight does not produce the desired result in these cases.

41. What is wrong? • define Debug(Input) [ • DebugStressToWeight( • NonFinal( Lapse( FootBin( MainStress( AlignLeft( • Clash( Input .o. Gen))))))) ]; • regex Debug({kalasteleminen}); • (ká*.las).te.(lè*.mi).nen <-- actual winner • (ká*.las).(tè*.le).(mì*.nen) <-- desired output • (jä´r.jes).tel.(mä`l.li).syy.(dèl.lä).ni • (jä’r.jes).(tèl.mäl).li.(sy`y.del).(lä`*.ni) • The StressToWeight constraint eliminates some of the desired winning candidates.

42. Conclusion • Can we get Ternary feet in Finnish “for free”, from the interaction of independently motivated principles? • We don’t know. • Optimality Prosody is computationally very difficult. • The number of initial candidates is huge: • kalasteleminen 70653 • järjestelmällisyydelläni 21767579 • Simple tableau methods do not work. • Finite-state implementation guards against errors made by a human GEN and EVAL. • But even when an error can be pinpointed, the fix is not obvious. • Debugging OT constraints is as hard as debugging two-level rules, in practice more difficult than rewrite systems.

43. Final Thoughts • Morphology is a regular relation. • The composition of words (morphosyntax), morphological alternations, and prosody can be described in finite-state terms. • A complex relation can be decomposed in different ways. • There are many flavors of finite-state morphology: Item-and-Arrangement, Rewrite rules, Two-level rules, Realizational Morphology, Classical optimality constraints. • Computing with finite-state tools is fun and easy. • We have sophisticated formalism for describing regular relations, efficient compilers and runtime software. • ‘Pen-and-pencil’ morphology badly needs computational support. • It is difficult to get globally correct results relying on a handful of interesting words, rules, and constraints.

44. References • Kenneth R. Beesley & Lauri Karttunen, Finite State Morphology, CSLI Publications. March 2003. (Software included). • http://www.fsmbook.com/ • Lauri Karttunen, "Computing with Realizational Morphology" in CICLing-2003, A. Gelbukh (ed.), Lecture Notes in Computer Science 2588, pages 205-216. Springer Verlag. 2003.