slide#1 slide#2 why language important is? …200.652/prosem/files/halberda,languageprosem.pdf ·...

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Language:Words and Syntax

Cognitive ProseminarBy: Len Taing

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Why language important is?• “When we study human

language, we areapproaching what somemight call the ‘humanessence’, the distinctivequalities of mind that are,so far as we know, uniqueto man.” -Noam Chomsky

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• Advantages of words:– large number of concepts (> 60,000)– rapid computation

• recognize spoken word: 1/5 second• retrieve word for production: 1/4 second

• Disadvantages of words:– finite number of predetermined concepts– everyone must have memorized them

The Lexicon

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• Advantages of syntax:- content neutral rules allow us to combineany noun with any verb

“Colorless green ideas sleep furiously”- rules allow new ideas to be expressed- the number of possible combinations growsexponentially with length of sentence

• Disadvantages of syntax:– rules require symbols, and perhaps the

mind is not a symbol manipulating machine(behaviorism & connectionism)

The Syntax

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The Lexicon• Children rapidly learn new words (yesterday)• Is this ability uniquely human?

No (e.g. Ai the chimp and other animals)• Are words symbols for both child and animal?

Behaviorists: No, all words are justassociations (Skinner etc)

Cognitivist: Yes for child, maybe foranimal (Chomsky, Pinker, Markman, Bloom etc)

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Design of Human Language

• Words for common entities– (mechanism = memory)

• Grammatical rules for novel combinationsof entities– (mechanism = on-line computation)

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The Syntax

Combinatorial grammar (Humboldt: “theinfinite use of finite media”)

• Two types of rules of grammar:--morphological rules, build new words

from parts--syntactic rules, build sentences from

words

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Syntax and morphology• Syntax/Grammar

– Sentences are thehighest level oflinguistic meaning

– Words combine in toform sentences

• Consider:• “Toad ate the cookie”• * “Cookie toad ate the”

– Sense ofgrammaticality andorder

• Morphology– Morphemes are the

lowest level oflanguage that conveymeaning

– Morphemes aremultiple phonemesthat combine to formwords

• Consider:• “re-gift-er”• *“gift-er-re”

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Where does the linguistic ordercome from?

elephant• Behaviorists (Skinner):

Learned through Associations

• Cognitivists (Chomsky):Innate syntax rules

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Language: The associativist story• Skinner, behaviorism, and

language: (stimulus response)– No innate knowledge– Children learn language b/c

adults/environment teach it– Parents provide corrective

feedback

• Grammar:– Word chain devices

• Morphology:– *morpheme chain device

• Language as statisticalprobability

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Associativist GrammarWord1 Word2 Word3 Word4Tall dogs sleep continuouslyFast wounds walk viciouslyGreedy farmers yell openlyPretty foam kicks genuinely

• P(Talldogs) = 0.95• P(sleep viciously) = 0.001• P(“Grammar is a complicated word chain device”)= 0.15• Chain the transitional probabilities to get a

sentence

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Associativist MorphologyMorph1 Morph2 Morph3Darwin ian ismKick er edTalk istEr kick

• P(Darwin + ian + ism) = 0.89• P(Kick + er) = 0.98• *P(er + Kick) = 0.0001

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Problem with word-chain devices(1)

• Separability of semanticsand syntax

• Chomsky: “Review ofverbal behavior” (1959)– S = “Colorless green ideas

sleep furiously”– P(S) = 0– Grammaticality: YES!

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Problem with word-chaindevices(2)

• Stimulus does not predict response: Validutterances.

-What a beautiful juggular.-Remember that one timeIn transelvannia?-I forgot today was daylightssavings time.

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Problems with word-chaindevices(3)

• Poverty of the stimulus• Consider all of the English sentences under 20

words.– e.g. “You have a finite set of rules that help you

generate and validate an infinite number ofgrammatical sentences.” (19 words)

• There are 10^30 such sentences. Even at a rateof memorizing 100 sentences a minute, after 1billion trillion years, you’ll only learn 1% of it!– But, kids acquire language within 5 years! They must

not be using associations

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Poverty of the Stimulus• How fast do children learn the rules?

≈ 3 years

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≈ 3 yearsThe Plural Rule

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≈ 3 yearsThe Plural Rule (children succeed at 2.5 years)

This is a wug.

Now there are two of them. There are two...Jean Berko (1959)

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≈ 3 yearsThe Past-tense Rule (children succeed at 3 years)

Pinker (1980)

• Every day we like to flibble.• Yesterday, we ….?

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Typical dialog• Child: My teacher holded the baby rabbits and we patted

them.• Parent: Did you say your teacher held the baby rabbits• Child: Yes• Parent: What did you say she did• Child: She holded the baby rabbits and we patted them.• Parent: Did you say she held them tightly• Child: No, she holded them loosely.

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The 2-Word StageWord Order (2 year olds)

Child says: “Dog big” (the dog is big)“Big Dog” (that is a big dog)“He big, Johnny big,” (he is big)BUT NEVER SAYS:“*Big he,” (*that is a big he*)

Paul Bloom (1990)

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Poverty of the Stimulus• Do parents provide corrective feedback?

No

• An Actual Parent-Child Dialog (sad parenting)• Child: Nobody don’t like me.• Parent: No, it’s nobody likes me.• Child: Nobody don’t like me.• 2 more iterations• Parent: Say, nobody likes me.• Child: Oh, Nobody don’t likes me.• Parents rarely give corrective feedback and when

they do it doesn’t work

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Lexicon and Syntax arelocalized in the human brain

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A simple theory:• Irregular forms are words:

bring sound: “brĭŋ” meaning:

brought sound: “brŏt” meaning: past tense

• Regular forms can be generated by a rule (combinatorial operation):

walk

V past tense

-ed

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-20

-15

-10

-5

0

5

10

15

20

1 2 3 4

Pro

po

rti

on

of

Prim

ing

Normal

Patient D.E.

Patient J.G.

Patient T.S.

RegularPast Tense

IrregularPast Tense

SemanticRelations

Double Dissociation Of Regulars and IrregularsMarslen-Wilson et al

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An Agrammatic Aphasic Patientslide#28Alternative

Artificial neural networks (connectionism)• There are no rules; just analogies from memory• Pattern associator memory: links sounds to sounds

instead of words to words

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Speech SegmentationHow do we find the Words?

Maybe there are spaces between them.

Where are the silences between words?

-J. Saffran

Statistical- what sounds usually go together

“pretty baby” NOT “pre tyba by”

slide#30Familiarization Preference Procedure

-Familiarize infants to an auditory stimulus(i.e. play it over and over until baby gets sick of it)

-Test if infants have learned anything about the stimulus(i.e. let the baby control what she hears)

90° 90°

Red ligh t Red ligh t

Yellow light

Video Camera Lens

Chair on which

parent and child sit

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Speech SegmentationStatistical cues:

from Saffran, Aslin, and Newport (1996)

-Familiarize 8-mnth-olds to a proto-language for 2 mintibudopabikudaropigolatupabikutibudogolatudaropidaropitibudopabikugolatu

-Testtibudopabiku vs pigolatudaro

7.5 sec 8.5 sec

Probability = .8 Probability = .2

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Language• Vast expressive power• The sources of this power:

cow sound: “kow” meaning:

Lexicon:Memorized words

(Saussure: the “arbitrarysign”)

Syntax:Combinatorial grammar(Humboldt: “the infinite

use of finite media”)

“Justin teaches class”

NP VP

Noun Verb Direct Object“Justin teaches class”

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Languages of New Zealand (as well as Latin)

-The boy kicked the ball.

Grammatical Structure

Subj. Verb Dir. Obj.

English

-The ball the boy kicked.-The boy the ball kicked.-Kicked the boy the ball.

-*Kicked the ball the boy.

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Tall dogs sleep continuouslyFast wounds talk viciouslyGreedy farmers yell openlyPretty foam kick genuinely

Rule based grammar

Adj. Noun Adv.Verb

• Grammar is built up from syntactic rules:– S NP VP S(NP(tall dogs) VP(sleep openly))– NP N NP(N(dogs))– NP adj. NP NP(adj(tall) NP(N(dogs)))– VP V adv. VP(V(sleep) adv(openly))

Learning grammar = Learning the orderly relations amongclasses of words.

slide#35Grammatical Structure

Use familiarization preference procedure

vs

Relations among classes of words

-Familiarize 8-mnth-olds to a proto-language for 2 min

from Marcus, Vijayan, Bandi Rao, and Vishton (1999)

AAB

-Test: new words

AABSame

strucure

ABBNovel

structure

6 sec 8 sec

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Paul Bloom; Word Order

Child says: “Dog big”Could mean “That dog is big”“Big Dog” (NP Adj and Adj N)Could mean “That is a big dog”“He big, Johnny big,” (NP N)Could mean “He is big, Johnny is big”BUT NEVER SAYS:“*Big he, *Big Johnny.” (*Adj NP)“*Big is he, Big is Johnny”

At the very beginning of the child making 2-word utterances

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Privileges of occurrenceChild says: “Dog big”“Big Dog” (NP Adj and Adj N)“He big, Johnny big,” (NP N)BUT NEVER SAYS:“*Big he, *Big Johnny.” (*Adj NP)

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Two-word Utterance Stage

• “Mommy sock”• “Billy up” “Sock foot” “Me happy.”Does the child distinguish N and NP at this

stage? Are “Mommy, Billy, me”syntactically distinguished from “sock?”“Sock” could be short for “the sock.”Could be a NP or a N. “Mommy, Billy, me”can only be N. (In adult grammar).

Privileges of occurrence

Child says: “Dog big”

“Big Dog” (NP Adj and Adj N)

“He big, Johnny big,” (NP N)

BUT NEVER SAYS:

“*Big he, *Big Johnny.” (*Adj NP)

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Do Animals have a syntaxNoBut some people are still looking

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Animal Lexicons

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Other Evidence For Innate Grammar:discussed in Pinker

•Specific Language Impairment:Genetic link

•Creolization in sign language andspoken language

•Differential loss of grammar followingstroke

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Language: the structure of meaningSyntax

Morphology

slide#43Two sets of rules:

Morphology Syntax

“Justin teaches class”

NP VP

Noun Verb Direct Object“Justin teaches class”

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What is a rule?

• Input-output function.• Operates over abstract variables. (E.g.,

N(noun), Nstem, Ninflection.)• N --> Nstem Ninflection“A noun can consist of a noun stem followed

by a noun inflection”

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Rule based morphology• Form Semantics Rule

-er (N) “someone who” V + erkicker, xeroxer

-ism (N) “ideal or belief” N + ismdarwinism, kickerism*

-ness (N) “state of being” Adj+nesblackness, ugliness

-’s (Det.) “of N” N + ‘sLen’s, kicker’s, ugliness’s

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Readings roadmapLanguage

SyntaxPinker: “How Language

Works”

MorphologyPinker: “Words, Words, Words”

Past Tense Debates:Pinker, Ullman: Rule-based view

McClellan, Patterson: Associativistor Connectionist view

Word LearningSaffrin, Aslin, Newport:“Statistical learning by8-month-old infants”

Marcus: “Rule learning byseven-month-old

Infants”

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Further prima facie evidence forrules

• Overregularization in childhood.• Both past tense and plurals:• Period of production of correct irregular

forms. (E.g., “we swam, we brought it)• Followed by period of overregularization

(E.g., “we swimmed, we bringed it.”

Marcus, G., Pinker, S., Ullman,M., Hollander, M., Rosen, T. J., &Xu, F. (1992) Monographs of the

Society for Research in ChildDevelopment 57(4).

Regular & Irregular Inflection

• Regular verbs: walked, jogged, patted, kissed• Predictable: verb + -ed• Open-ended:

– faxed– snarfed, moshed, spammed, dissed

• Productive in children:– wugged– bringed

Marcus, G., Pinker, S., Ullman, M., Hollander, M., Rosen, T. J., & Xu, F. (1992) Monographs of theSociety for Research in Child Development 57(4).

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• Irregular verbs: brought, hit, went, sang,slept, made, rang, flew

• Unpredictable:– sink-sank– cling-clung– think-thought– blink-blinked

• Closed class: 165 irregulars; no recent newones

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A Developmental Story

• Children overregularize when they learnthe rule!

• Problem--why do they stopoverregularizing?

• Why don’t adults apply the rule to “bring-bringed.”

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Blocking

• Retrieved irregular inflection blocksapplication of the rule.

• Do children have to learn blocking?

NO NEGATIVE EVIDENCE. CHILDRENARE NOT CORRECTED FORGRAMMATICAL ERRORS

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Corrections of child language

• Where is that big piece of paper I gaveyou yesterday?

• Child: Remember I writed on it.• Oh that’s right. Don’t you have any paper

down here buddy?

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A Simple Explanation forChildren’s Errors

• Children’s memory retrieval is less reliablethan adults’.

• If the child fails to retrieve an irregular, andthe child has the rule, the child applies therule to the irregular.

Marcus, G., Pinker, S., Ullman,M., Hollander, M., Rosen, T. J. &Xu, F. (1992) Monographs of the

Society for Research in ChildDevelopment, 57.

Evidence:

• Overregularizations are rare (< 10 %overall)

• Memory is weak:– The less often a parent uses an irregular, the

more often the child errs on it (19/19 children,p < .001)

• Rule has been acquired:– Errors with irregulars don’t appear right away,

don’t appear until children are reliablyproducing regulars

Marcus, G., Pinker, S., Ullman, M., Hollander, M., Rosen, T. J., & Xu, F. (1992) Monographs of theSociety for Research in Child Development (57)4.

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Conclusions

• Blocking is innate.-- If irregular is retrieved, it’s used.--No negative evidence

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A Complication:Patterns in the Irregular Verbs

• Irregular verbs display patterns:– keep-kept, sleep-slept, feel-felt, dream-dreamt– wear-wore, bear-bore, tear-tore, swear-swore– string-strung, swing-swung, sting-stung, fling-flung

• Patterns are occasionally generalized:– Children: brang, bote, wope– History: quit, caught, snuck– Dialects: clumb, swole– Sophomores: spling-splung

Xu, F. & Pinker, S. (1995) Journal of Child Language, 22, 531-556.Prasada, S. & Pinker, S. (1993) Language and Cognitive Processes, 8, 1-56.

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Alternative

• Both “dog” and “dogs” are memorizedwords. “Dogs” marked for plural.

• Both “walk” and “walked” are memorizedwords. “Walked marked for past test.

“Child,” “children” work this way.“Bring” and “brought” work this way.

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Alternative: Rule following onlyapparent

• Swimmed by analogy to “rimmed,”• Walked by analogy to “talked”,…. Sheer frequency of regulars leads them

to have more analogies.Explains occasional overgeneralization of

irregulars.

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Arguments for Pinker’s wordsand rules theory

• 1) Linguistic phenomena in derivationalmorphology

• 2) Evidence for innate knowledge of levelordering.

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Peter Gordon’s Level OrderingStudy

The x-eater. A monster.

This is a child. These are -----.The monster likes to eat -------.He’s a ….. “children-eater,”Or “child-eater.

This is a rat. These are ----The monster likes to eat ------He’s a “rat-eater,” not *“rats-eater.”

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Poverty of Stimulus

• In input, there were 0 instances of adultsusing irregular plurals in compounds.

• Conclusion: distinction between regularand irregular inflection and level orderingrules innate.

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A third problem:

• Pattern associators generalize apattern only when it is frequent in input(word types); people can generalize aregular pattern even when it is rare:– Studies of regularization in children– Studies of regularization across languages

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Crosslinguistic Studies

• Regular verbs are the majority in English.• Perhaps the regular pattern is generalized

most freely simply because it is mostfrequent.

• Needed:– A language where a regular (default) rule

applies to a minority of forms.

Marcus, G., Brinkmann, U.,Clahsen, H., Wiese, R., & Pinker,S. (1995) Cognitive Psychology

29, 189-256.

The Exception that Proves theRule

English –s (99.6%) German –s (7%)• weird Ns (ploamphs) •weird Ns (Plaupfs)

• names (the Julia Childs) •names (die Thomas Manns)

Marcus, G., Brinkmann, U., Clahsen, H., Wiese, R. & Pinker, S. (1995) Cognitive Psychology, 29, 189-256.

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Marcus, G., Brinkmann, U.,Clahsen, H., Wiese, R., & Pinker,S. (1995) Cognitive Psychology

29, 189-256.

The Exception that Proves theRule

English –s (99.6%) German –s (7%)• weird Ns (ploamphs) •weird Ns (Plaupfs)

• names (the Julia Childs) •names (die Thomas Manns)

• eponyms (Batmans) •eponyms (Fausts)

• regularization errors (mans)

•regularization errors (Manns)

Marcus, G., Brinkmann, U., Clahsen, H., Wiese, R. & Pinker, S. (1995) Cognitive Psychology, 29, 189-256.

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Words and Rules in the Brain

• Neural substrate of word memory shouldbe tied do irregulars

• Neural substrate of grammaticalcomputation should be tied to regulars

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• A. Anomia: Impaired word-finding;relatively unimpaired grammar– Irregulars (63%) harder than regulars

(85%)–Regularization errors (25%)–Could do wug-test (80%)

• replicated by Tyler et al., 2001, on HSEpatients w/ temporal lobe damage

Ullman, M., Corkin, S., Coppola, M., Hickok, G., Growdon, J., Koroshetz, W. , & Pinker, S. (1997)Jounral of Cognitive Neuroscience, 9, 289-299.

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• Agrammatism: Impaired grammar; lessimpaired word-finding– Irregulars (69%) easier than regulars

(20%)–Few regularization errors (0%)–Could not do wug-test

–A DOUBLE DISSOCIATION


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B. Alzheimer’s Disease: Impaired memory;relatively unimpaired grammar.

• Irregulars harder than regulars (60% v.89%)

• Regularization errors (27%)

• Can do wug-test (84%)


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Parkinsons’ Disease: Agrammatic symptoms;less impaired word-finding.

• Irregulars easier than regulars (80% v.88%)

• Few or no regularization errors (0%)

• Difficulty with wug-test (65%)


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Conclusion:

• Expressive power of language comesfrom an interaction between the mentallexicon (memory) and the mentalgrammar (computation)

• Irregular and regular inflection contrastthese processes, holding meaningconstant

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• Regular inflection is applied whenever memoryfails:– difficult-to-analogize words (ploamphed, frilged)– words with inaccessible roots (low-lifes, flied out)– words poorly recalled by children (breaked, holded)– words poorly recalled by patients with disorders of

word retrieval (anomia, Alzheimer’s)

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Word learning problem

• Parsing individual words from continuousspeech– Misconception: adults make the boundaries

clear for the child– People don’t speak like Frankenstein

• Foreign language speech (demo)

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Word parsing summary• Statistical boundary

– Infant use statisticalpatterns betweenphonemes todetermine wordboundaries:

– P(“ca” + “t”) = 0.75 (noa word boundary)

– P(“ph” + “z”) = 0.001(a word boundary)

• Purely statistical, noneed for rules

• Rule based boundary– Infants can learn rule

based patterns inwords

– e.g. AAB phonemepattern “dodoba”

– *important: can detectviolations of that rule

• Rules and statisticallearning are two toolsin infants’ toolbox

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Saffran, Aslin, Newport (1996)

• Speech stream (demo)– Continuous– Computer generated (no intonation)

• Result: infants use statistical patterns todetermine word boundaries

• Aside: Hauser has conducted a similarstudy with tamarin monkeys– Result: tamarin monkeys also are statistical

learners

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Marcus (1999)

• Statistical learning is not the only toolchildren can use in language acquisition

• There is also a rule based system thatthey use to learn.– E.g. AAB rule (demo)

• Read the paper to see how he establishesthis.

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Works”






Infants”

Domain general learning ability and syntax

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Works”






Infants”

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English past tense debate: Theproblem

• “He likes to… “Yesterday he…”gorpdancetringgofo

• English has 180 irregular verbs-– Small enough to memorize?– Amenable to rules?

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English past tense debates: Theproblem(2)

• “He likes to…” “Yesterday he…”gorp gorpeddance dancedtring tringed/tranggo wentfo foed

• Regulars: (rule-governed)– Add –ed: e.g. dance danced

• Quasi-regulars: (rule-governed irregulars)– Singsang, ringrang, sleepslept, keepkept

• Whacky irregulars:– Go went. Note: no generalization for “fo”

Systematic

Arbitrary

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Past tense: a rule based story• Pinker, Ullman: WR theory

– Whacky irregulars: gowent (memory)– Two components:

• rule based system(default): V + ed• lexicon (i.e. associative memory).• When there is a trace in lexicon, it pre-empts the rule-based

default• When memory fails mistake in speech: gogoed

– Middle-road: has a component that explainssystematicity and arbitrariness of past tense forms

• Explains the quasi-regular memory with a connectionist story– It’s a story of how short-term memory works

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Past tense: an associative learningtheory

• Rummelhart, McClelland– Connectionist model– Past tense domain– *Phoneme to phoneme associations

• Nothing else, i.e. no rules, just statistics

• State of machine (connection weights,input, and connections) determines theoutput

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Connectionism and neural nets: anintroduction

• Neural networks:– Nodes (computing centers/neuronal bodies)– Connections (links between nodes/axon-dendritic connections)– Nodes sum up all of the input from the connections, and based

on an internal function will either fire or not– Connections can be weighted according to strength

• Positive: excitatory• Negative: inhibitory

– Back-propagation algorithm: learning of connection weights thathelp minimize error in the experience set

• More powerful than word chain devices b/c ofgeneralizability– i.e. connection weights + back-prop learning might lead to

“expected” output for novel input

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Connectionism: AND-net

• Demonstration of a neural network thatcomputes the AND function

• Logical AND: 0 = false, 1 = trueA B Result0 0 01 0 00 1 01 1 1

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Connectionism and neural nets: anintroduction(2)

rin sin ing ng#

#sa sin ing ng#

#dr #ra #ri #sai

#dr #ra #ri ang

dri ing ink#si

#si dri ink rin

Input layer representing base form (input to computation: phoneme)

Output layer representing past tense form (result of computation:phoneme)

Connection (layer)

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Connectionism: its just ComputerScience

• These models get bigger and more complicated– To point, where trust statistical invariants

• Can be made to perfectly match the training set• But the test is on novel input• Model has the ability to learn, adjust connection

weights– Back-prop is just on such learning algorithm– Hebbian

• Models can also have fixed connection weights

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Take home message

• You will note that the tension between the view thatlanguage is rule based, and that language comes fromassociative learning is rooted in the fact that language isboth systematic and arbitrary

• Connectionist models are statistical learners• Saffran, Marcus:

– Statistical and rule based learning a domain general capacitythat, in this case, was co-opted for language acquisition?

• Pinker, Ullman vs. McClelland, Paterson– Is the English past tense best explained by rule-based or

associative system?– Is there a middle ground?

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Language and lobster dancing arefun! Questions?

Hi little lady, do youjitterbug?

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