The Competition Model Brian MacWhinney- CMU Elizabeth Bates Janet McDonald Kerry Kilborn Judit Osman-Sági Vera Kempe Yoshinori Sasaki Csaba Pléh Antonella Devescovi Takehiro Ito Jeffrey Sokolov Arturo Hernandez Michèle Kail Klaus-Michael Köpcke Ovid Tzeng Beverly Wulfeck Ping Li Empirical Results Published in: MacWhinney, B., & Bates, E. (Eds.) The crosslinguistic study of sentence processing. New York: Cambridge University Press, 1989. 15 articles since then 1 1. The Input A. Lexical Functionalism -- constructions B. Input-driven Learning -- cues, frequencies Cue validity predicts cue strength [p(function)|form] - comprehension [p(form)|function] - production 2 2. The Learner Distributed representations -> transfer Emergent modularity Neuronal commitment, automaticity Capacity Functional neural circuits Perspective-taking 3 3. The Context Classroom context Negative feedback is positive feedback Instructional format interacts with learner characteristics Role of computerized instruction Setting up input contexts Role of lexical richness Learner must learn how to learn 4 1A. Lexical Functionalism Form (cue, device) Function (role, meaning) 5 Competition between devices Competition between interpretations Agent Marking competition Patient Marking hidden Agent Function competition Patient Function 6 Cue validity -> cue strength Cues -> Interpretations Comprehension Meanings -> Devices Production pre agr init nom the giv def hidden act top per 7 Some cues The tiger pushes the bear. The bear the tiger pushes. Pushes the tiger the bear. The dogs the eraser push. The dogs the eraser pushes. The cat push the dogs. Il gatto spingono i cani. 8 The dog was chased by the cat. Comprehension - Interpretations compete Agent: The dog vs. the cat Patient: The dog vs. the cat Production - Devices compete Dog placement: preverbal, postverbal, by-clause Cat placement: preverbal, postverbal, by-clause 9 Cue interactions • • • • • Peaceful coexistence Cue coalitions Competition between interpretations during comprehension Competition between devices during production Change from category leakage and reinterpretation 10 Cues vary across languages English: The pig loves the farmer SV > VO > Agreement German: Das Schwein liebt den Bauer. Den Bauer liebt das Schwein Case > Agreement > Animacy>Word Order Spanish: El cerdo quiere al campesino. Al campesino le quiere el cerdo. "Case" > Agreement > Clitic > Animacy > Word Order 11 Exotic Patterns Navajo: *Yas lééchaa’í yi-stin. snow dog him-frooze. Lééchaaa’ yas bi-stin dog snow him-frooze 7-level hierachy of Animacy -- switch reference 12 Basic results Reliable Cues Dominate Cue Strengths Summate Competition Cells show most variability 13 Ungrammaticality Continuity for pockets of grammaticality Hungarian possessive for accusative Croatian neutralized case in masculine Japanese “wa” marking Slowdown for grammatical sentences in Russian, Hungarian, Spanish without the “preferred cue” Cue summation for pronominal processing 14 English Word Order Language by Word Order Cognition (1982) 100 Perce ntage choice of first noun 80 German 60 Italian 40 20 English 0 NVN VNN NNV 15 Italian Agreement Language by Agreement JVLVB 1984 100 Perce ntage choice of first noun 80 60 German 40 English 20 Italian 0 Ag0 Ag1 Ag2 16 English Children English 60 50 Word Order 40 30 20 10 Anim acy Agre emen t 0 2 3 4 5 Adu lt Age 17 Hungarian Children Hungarian 50 Cas e % choice first noun 40 30 20 Wo rd Or der 10 Anim acy 0 3 4 5 6 Age 18 Italian Children Italian 60 50 Agreem ent 40 Anim acy 30 20 Word Order 10 0 2 3 4 5 Adu lt Age 19 Cue validity (low levels) Task frequency F(task T) / F(all tasks) Simple availability (relative availability of a cue for a given task) F(times when cue A is present) The cat chases the dog. Contrast availability F(cue A present ^ cue A contrasts) The cat chases the dogs. 20 Cue validity (high levels) Simple reliability Reliable if always leads to right functional choice F(cue A present ^ cue A contrasts ^ cue A correct) / F (cue A present^cue A contrasts) Conflict reliability In certain contexts, one cue will be more reliable F(cue A conflicts with other cue ^ cue A wins) / F(cue A conflicts with any cue) SA -> CA -> SR -> CR transition 21 Cue validity vs. cue strength Cue validity is based on (tedious) counts of texts Cue strength is first assessed through ANOVA analyses in Competition Model experiments Cue strength is then modeled using MLE 22 MLE models of cue strength P (first noun) = ∏ S i (first) / ∏ S j (others) Two choice case P (first noun) = ∏ S i (first) /∏ S i (first) + ∏ S j (second) Models vary number of parameters and can be additive or multiplicative 23 Pronouns - an online example MacDonald and MacWhinney (1989) Just before dawn, Lisa was fishing with Ron in the boat, and she caught a big trout right away. and lots of big trout were biting. Priming of referent at 500 msec for unambiguous gender. Slowdown in processing of probes right at 0msec delay when there is a gender contrast only. 24 Pronouns - implicit causality McDonald and MacWhinney (1994) Probes presented at 4 Delay Times: D1 * 100 * D2 D3 pro * 200 D4 * end * Gary amazed Ellen time after time, because he was so talented. N1 Probes: V N2 filler referent non-referent distractor verb , because PRO predicate. Gary Ellen Frank amazed Joel admires Susan because she is so fabulous. 25 Results and Competition 1. Slowdown in processing of probes at pronoun when there is a contrast. 2. Facilitation from pronoun onwards when first noun advantage agrees with implicit causality. 3. Activation of N2 right at the pronoun for E-S verbs! 4. Standard Competition Model cue summations and competitions, all right when they should occur. 26 2. The Learner Distributed representations -> transfer Emergent modularity Neuronal commitment, automaticity Capacity Functional neural circuits Perspective-taking The black dog is going to the market with his owner. 27 Parasitic Learning -- Kroll “turtle” Translation route “tortuga” 28 The Revised Hierarchical Model Kroll & Stewart, 1994 lexical links L1 L2 conceptual links conceptual links concepts 29 Transfer Principle: Everything that “can transfer” will. Connectionism predicts transfer Word order can transfer Phonology can transfer Meaning can transfer Morphological markings cannot Early bilinguals as mixed 30 Transfer beyond the word I want to go to school. Yo querer ir a escuela. I would like to go to school. (I) would-like to-go to the-school. xx quer-rí-a ir a la-escuela. Do you want to eat at my house? You want not want at me eat, huh? Translation with feedback may not be so bad. http://psyling.psy.cmu.edu/traducir/ 31 Problems with Transfer Lexical concepts “sibling” in Dutch = brother or sister Broadness of application of translation equivalents glass in English, vidrio or vaso in Spanish car - “achterbak” or “kofferbak” tree -“stam” or “boomstronk” body - “romp” snout - “slurf” 32 More Problems with Transfer • Grammatical expression of certain aspects of experience The boy had fallen from the tree and his dog was hovering over him Semantic boundaries differ across languages prepositions (Ijaz, 1986) Germans under-emphasize contact and overemphasize movement for “on” German “auf” means “up” 33 Emergent modularity Growing modules Farah and McClelland Jacobs, Jordan, Barto Kim et al. fMRI study 34 Capacity restrictions Detectability Complexity (for production) Assignability (memory load) Online load minimization One good cue is enough (Russian, Spanish) Waiting for a reliable cue: Russian, Hungarian No use waiting for cue that will not be reliable, German die Frau küßt der ... 35 DutchL1 EnglishL2 Mean Perce nt first nou n choice 10 0 90 80 70 60 Group 1 50 Group 2 Mono ling uals in 40 Eng lish 30 20 10 0 NVN VNN NNV Fi g 8.5 Group x word o rder i ntera cti on i n Eng lish 36 JapaneseL1 EnglishL2 100 Novice JE 2 90 Mean percent first noun choice 80 Monol ing ual Japanese Advanced JE2 Monol ing ual Engl ish 70 60 50 40 30 20 10 0 NVN VNN NN V Fig 8.7 Group xword order interaction in Eng l ish 37 EnglishL1 DutchL2 10 0 Percentage vari ance acco unte d fo r 80 60 Noun ani macy Case inflection Wo rd ord er 40 20 0 Eng lish E/D 1 E/D 2 E/D 3 Dutch 38 DutchL1 EnglishL2 100 Percentag e vari an ce accou nted fo r 80 60 Noun Animacy Case Inf lection Word Order 40 20 0 Dutch D/ E 1 D/ E 2 D/ E 3 English Gro up 39 Aphasics - Word Order Language x Group x Word Order Brain and Language (1986) 100 Percentage Choice of FIrst No un 80 Italians 60 English Broca 40 English Normals 20 0 NVN VNN NNV Wor d Or der 40 Aphasics - Agreement Language x Group x Agreem ent Brain and Language (198 6) 100 Percentag e Ch oice o f F irst No un 80 60 Engl ish Broca 40 Ita lian Broca Engl ish No rmal 20 Ita lian Normal 0 Ag0 Ag1 Ag2 Agreemen t 41 Case in Croatian Normals Cas e x Anima cy in Se rbo-Croatia n Norma ls 120 100 Percentag e Ch oice o f F irst No un 80 AA 60 AI IA 40 20 0 Nom-Acc Acc-N om Ambiguous Case 42 Case in Croatian Aphasics Cas e x Anima cy in Se rbo-Croatia n Broca 's 100 80 Percentag e Ch oice o f F irst No un AI 60 AA 40 IA 20 0 Nom-Acc Acc-N om Ambiguous Case 43 Word Order in Production Wor d Or der in Br oca' s Aph asics 100 G E I T 80 Percentage U se 60 Turki sh Ital ian German Eng li sh 40 20 E T G I E G I T 0 SVO SOV Other 44 Some generalizations Children learn the most valid cues first. Aphasics preserve the most valid cues. They also rigidify on the strongest devices L2 learners attempt transfer, but then learn cues. They gradually reach L1 levels of cue strength. Connectionism predicts transfer. 45 3. The Context Providing negative evidence go + PAST meaning competition word episodic support word analogic pressure went episodic support competition go + ed analogic pressure 46 Word learning - Merriman demitassse episodic support competition cup extensional pressure 47 Recovery in syntax Dative Role competition to ___ “to” episodic support verb episodic support V + NP + NP extensional pressure 48 Complex cases "pour arg1 arg2 arg3 " competition "1 pours 2 into 3" lexical frame group frame: 1 verbs 2 into 3 "1 pours 3 with 2" group frame: 1 verbs 3 with 2 49 MacDonald et al. 50 MacDonald et al. 51 Open issues Neuronal Commitment Social Identification Resonance Setting up Input Contexts 52 Conclusions Models of Input, Learner, and Context must interlock Competition Model is properly accounts for what we know about language learning, but The model must be developed still further. 53