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Learning Alternation without Bias

Learning Alternation without Bias . Young Ah Do MIT youngah@mit.edu WCCFL 29 April. 22-24. 2011 . Learning the Pattern of Alternation . Alternation: the realization of the same morpheme in various phonological contexts. l ike[ t ] buzze [ d ] hunt[ ɪd ]

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Learning Alternation without Bias

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  1. Learning Alternation without Bias Young Ah Do MIT youngah@mit.edu WCCFL 29 April. 22-24. 2011

  2. Learning the Pattern of Alternation • Alternation: the realization of the same morpheme in various phonological contexts. • like[t] buzze[d] hunt[ɪd] • Learning alternation • Korean noun inflection Young Ah Do, MIT

  3. Korean Noun Paradigm • Stem-final obstruents • UR /k’oth/ (Ko 1989) • [k’ot] ‘flower’ • [k’oth-ɨl]~[k’os-ɨl] [k’och-ɨl], [k’oc-ɨl] ‘flower-acc’ (Hayes 1998, Albright 2005, Choe 2004) • Stem-final nonobstruents • UR /pal/ • [pal] ‘foot’ • [paɾ-ɨl] ‘foot-acc’ intersonorant flapping Young Ah Do, MIT

  4. Learning Challenge: Obstruent–final Nouns • Phonotactically unpredictable • An order of usage frequency • s >>ch, th>> c, t (Jun 2007) • Different preference for each suffix • ch-ɨl >> th-il vs. th-e>> ch-e (Jun 2007) • Type frequency highest for lateral final nouns. (Kenstowicz & Sohn 2007) Young Ah Do, MIT

  5. Learning Stages of Alternations • Children (4;2-7;8) produce adult inflection of obstruent-final nouns slower than nonobstruent-final nouns (Do, ms). • Nonobsruent-final nouns: Identical inflectional form across all age groups. • Obstruent-final nouns: Three-stage learning Young Ah Do, MIT

  6. Production of Obstruent-final Nouns • Three-stage learning • Adults : Variations [k’os-ɨl] ~ [k’och-ɨl] ~ [k’oth-ɨl]‘flower-acc’ • 4;2-5;6 : Attempt an isolation form [k’ot] • 6;2-7;8 : Most frequent adult form [k’os-ɨl] Young Ah Do, MIT

  7. Goal • Predict three-stage learning by training a learner with • Constraint-based grammar • The statistical distribution of alternations without • Assuming intrinsic bias Young Ah Do, MIT

  8. Overview • Alternations in Korean noun paradigms and three-stage learning • Analysis • The initial stage is due to incorrectly promoted Output-Output Faithfulness constraints (McCarthy 1999). • The intermediate stage results from demoting Output-Output Faithfulness constraints (OO-F). Young Ah Do, MIT

  9. Overview • MaxEnt Grammar Tool (Hayes 2009) • Simulation • Constraints: OO-F, Markedness, and IO-F constraints. • Type frequency of adult variants in corpus • Learning alternations without bias Young Ah Do, MIT

  10. Korean Noun Paradigm • Three-way laryngeal contrast among obstruents (Jun 2009, p.3) Young Ah Do, MIT

  11. Alternations in Nouns • Neutralization of obstruents to their homorganic lenis stop counterparts in coda position • /suph/ [sup] ‘forest’ • /path/ [pat] ‘field’ • /puəkh/ [puək] ‘kitchen’ Young Ah Do, MIT

  12. Variation in Nouns • Prevocalic allomorphs of the noun stems show variation in final obstruents. Young Ah Do, MIT

  13. Observations about Variation • Variants: [s, th, ch, c, t], excluding tense consonants. • [s] >> [ch], [th] >> [c] , [t] • [ch]-ɨX >> [th]-ɨX • [th]-eX >> [ch]-eX • Relative frequency of variants matches corpus frequency (Jun 2009). Young Ah Do, MIT

  14. Experimental Results • Adults • Variation matchescorpus frequency • Young (4;2-5;6) • Attempt unmarked forms. • [pas-ɨl] ‘field-acc’  [pat], [pat an-ɨl] ‘field inside-acc’ Young Ah Do, MIT

  15. Alternation at Initial Stage Young Ah Do, MIT

  16. Alternation at Intermediate Stage • Intermediate (6;2-7;8) • Attempt the most frequent variant among adult forms. • Nom: [s-i] • Acc: [s-ɨl] • Loc: [s-e], [th-e] • Source: [th-esə] Young Ah Do, MIT

  17. Alternation at Intermediate Stage Young Ah Do, MIT

  18. Learning Path • The pattern of production Young: Unmarked form  Intermediate: The most frequent variant  Adults: Variants with different preference Young Ah Do, MIT

  19. The 1st stage: Unmarked form • The unmarked form is the most frequent in child directed speech • Unmarked 75%, Nom 20%, Acc 5% (I. Lee 1999) • But, this is not a frequency effect. • Children do know both unmarked and correct inflected forms. • Children innovate [d-i], [d-ɨl] and [d-e] by incorrectly choosing the unmarked form, rather than choosing the most frequent form. Young Ah Do, MIT

  20. Faithfulness to a Base • Claim: Child avoidance and selection • In order to satisfy highly ranked OO-F constraints (McCarthy 1999). • Assumption: unmarked form as a base of Korean noun paradigm (Albright 2008). • BD-Ident constraints, a kind of OO-F, start high in children’s grammar. Young Ah Do, MIT

  21. BD-Ident and Child outputs • BD-Ident[obs,cor]/_[+high,-back, +syl] >> *[obs,cor][+high,-back, +syl] Young Ah Do, MIT

  22. Toward Adults’ Stage • Claim • Child outputs are due to wrongly promoted BD-Ident constraints. • Adults’ grammar • BD-Idents constraints are demoted to their target low ranking (i.e., Markedness >> BD-Ident) • Intermediate stage • Attempt on the most frequent variant. • (maybe add something here)? Young Ah Do, MIT

  23. Question • Question • Assuming a set of BD-Ident, Markedness, Ident-IO constraints, and assuming an input corpus with alternations of varying frequencies, do we predict a three-stage learning process? • Answer: Yes! • (Assuming learning alternations as ranking constraints in their target positions, how can a learner re-rank constraints correctly?) Young Ah Do, MIT

  24. The Goal of Learning Simulation • To see if children can learn alternations purely by the distribution of alternations. • Specifically, • The more a given alternation occurs in the data, the more the relevant BD-Ident constraints will be demoted. Young Ah Do, MIT

  25. The Learner • Given • Grammar consisting of a set of constraints with initial weight • Initial weight: BD-Ident >> M >> IO-F (McCarthy 1999, ? for M >> IO ) • Constraints based on feature specification BD-Ident (Base as unmarked form :Albright 2008) Markedness IO-F (Input as underlying form: Ko 1989) Young Ah Do, MIT

  26. Learning as Weighting Constraints • Given • Outputs with frequency • Frequency of variants according to Corpus count (Jun 2009) • Learning • The learner encounters surface forms violating constraints • Violation of constraints are accessed by Perl script. Young Ah Do, MIT

  27. Weighting Constraints • Learning • Weight constraints according to the frequency of violations in the data. • Weighting constraints • Using MaxEnt (Maximum Entropy: Goldwater & Johnson 2003) • MaxEnt Grammar Tool (Hayes 2009) • After learning • A set of trained (MaxEnt) weights for a grammar • the predicted probabilities assigned to each candidate Young Ah Do, MIT

  28. Weighting Constraints using MaxEnt Young Ah Do, MIT

  29. Learning Data • Korean nouns • Obstruent-final (labial, coronal & velar) • Lateral-final • Nasal-final • Inflection • Nominative : -i • Accusative : -ɨl • Locative/goal : -e • Locative/source : -esə Young Ah Do, MIT

  30. Learning Phonotactics • Phonotactics • Intersonorant flapping: tal taɾ-i ‘moon-nom’ • Intersonorant voicing : pap  pab-i ‘rice-nom’ mak  mag-i ‘scene-nom’ • Palatalization : tikɨt tikɨci ‘alphabet [t]-nom’ kɨth  kɨch-i ‘end-nom’ mas  maʃ-i ‘taste-nom’ Young Ah Do, MIT

  31. Learning Alternations • Alternations of obstruent-finals • Violation of BD-Ident: [t]  [s, ch, th, c, t] • Violation of IO-F: /s, ch, th, c, t/  [s, ch, th, c, t] • Alternations of non-obstruent-finals • Violation of BD-Ident: [p,k]  [ph, kh, k’] • Violation of IO-F: /ph, kh, k’/  [p, k] Young Ah Do, MIT

  32. Three Age Groups • Simulation of different age groups • The older, the more inputs they get. • An example of accusatives • Ratio adapted from corpus count s 52%, ch21 %, th 18%, c 2 %, t 0% 5.2, 2.1, 1.8, 0.2, 0 .. 52, 21, 18, 2, 0 …… 5200, 2100, 1800, 200, 0 Young Ah Do, MIT

  33. The 1st Stage • BD-Ident >>M >> IO-F Interaction of BD-Ident and Markedness constraints. • IO-F constraints are too low to influence the outcome. • URs (Input) are assumed to be discovered later (ref ?). Young Ah Do, MIT

  34. The 1st Stage • Mastery of some phonotactics • Intersonorant voicing *[+son][-v][+son] >> *[+son, +v] >> BD-Id [v] • Intersonorant flapping *[+son][+lat][+son] >> *[ɾ] >> BD-Id [lat] • Partial mastery of palatalization *[+son][+ant, -dis][+son] >> *[ʃ] >> BD-Id [+ant,-dis] *[th][+high, -back, +syl] >> BD-Id [th]/_ [+high, -back, +syl] Young Ah Do, MIT

  35. Faithful Form to a Base • No mastery of palatalization [ti]  [ci] BD-Id [obs,cor]/_ [+high, -back, +syl] >> *[obs,cor][+high, -back, +syl] • The most probable outputs that the grammar predicts • Nom: d-i (illegal) • Acc: d-ɨl (unattested) • Loc: d-e(unattested) • Source: d-esə (unattested) Young Ah Do, MIT

  36. Success of Predicting Child Forms • Predicted forms are what young children attempt in early stage. • [pat] unmarked • [pad-i] using base form • Finding • Young children’s outputs are predicted by feeding the learner a small number of alternation data of Korean. Young Ah Do, MIT

  37. The 2nd Stage Feeding more data …… Young Ah Do, MIT

  38. The 2nd Stage • IO-F constraints are still inactive. • Mastery of palatalization BD-Id [obs, cor]/_ [+high, -back, +syl] >> *[obs, cor][+high, -back, +syl] • Mastery of some alternations Young Ah Do, MIT

  39. The 2nd Stage • The most probable outputs are the most frequent adult variants, in general. CorpusSimulation s-i s-i s-ɨl s-ɨl s-e, th-e th-e th-esə s-esə Young Ah Do, MIT

  40. The Final Stage Feeding more data …… Young Ah Do, MIT

  41. The Final Stage • M >> BD-Ident • Some M constraints remain higher than IO-F constraints and some are demoted. • Variation predicted! Young Ah Do, MIT

  42. Predictability of Variants • /path-e/ Observed Predicted • [path-e] 74350.5614804325079656 • [pas-e] 2165 0.3885079149244645 • [pach-e] 120 0.056734328452862 [pad-e] 0 1.0198046038491932E-9 • [pac-e] 20 3.0068321707463542E-4 Young Ah Do, MIT

  43. Predicted Preference • Pattern match with corpus • Overall • [s] >> [ch], [th] >> [c] , [t] • Before –e, -esə • [th-e] >> [ch-e], [th-esə] >> [ch-esə] • Before -ɨl • [ch-ɨl] >> [th-ɨl] Young Ah Do, MIT

  44. Conclusions • Child form due to highly ranked OO-F constraints. • Children can demote constraints just by exposing the rankings to probabilistic data from an adult speech corpus. • That is, without intrinsic bias, the statistics of Korean give rise to the attested learning stages. Young Ah Do, MIT

  45. Simpler Modeling? • Simpler alternative without any reference to OT or OO-F constraints? • Children use the frequencies of alternant to determine which phonological rules to acquire first (suggested by anonymous WCCFL reviewer). Young Ah Do, MIT

  46. Simpler Modeling ? • Pre-[-ɨl] constraints (Jun 2007) • s/_ɨl >> ch/_ɨl >> th/_ɨl >> c/_ɨl, t/_ɨl • p/_ɨl >> ph/_ɨl • k/_ɨl >> kh/_ɨl Earlier Later Young Ah Do, MIT

  47. Evidence for arguing against this proposal?? Young Ah Do, MIT

  48. Reference Young Ah Do, MIT

  49. Thanks Young Ah Do, MIT

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