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The emergence of linguistic productivity. Holger Diessel University of Jena holger.diessel @uni-jena.de http://www.holger-diessel.de/. Linguistic productivity. Language is productive. What underlies the productive use of language?. Standard answer: A linguistic rule.

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the emergence of linguistic productivity

The emergence of linguistic productivity

Holger Diessel

University of Jena

holger.diessel@uni-jena.de

http://www.holger-diessel.de/

linguistic productivity
Linguistic productivity

Language is productive.

What underlies the productive use of language?

Standard answer: A linguistic rule.

What exactly is a rule?

the acquisition of the english past tense
The acquisition of the English past tense
  • What is linguistic productivity (or what is a linguistic rule)?
  • How does linguistic productivity emerge?
slide5

Overgeneralization errors

buy  buyedhit  hittedbring  bringedgo  goed (wented)foot  foots (feets)child(ren)  childrens

slide6

Overgeneralization errors

1. Children produce the correct forms: went, kissed, saw

2. Children overgeneralize the regular past tense form: ringed, sayed. But only 2% of all irregular verbs are regularized. Great variability.

3. Children produce the correct forms.

slide7

U-shaped development

Overgeneralizations (2%)

correct (2,6)

correct (3;5)

slide8

Berko (1958) The wug test

This is a wug.Now there is another one. There are two of them.There are two __ .

6-7 year olds

slide9

Berko 1958

This is a man who knows how to rick.He is ricking. He did the same thing yesterday.What did he do yesterday?Yesterday he __ .

berko 1958
Berko 1958
  • Performance is not consistent.
  • Forms with [@d] are less often regularized than forms with [t] and [d].
  • Real irregular English verb forms (i.e. ring) are less often regularized.
slide14

Rules

What did the children learn?

-> A linguistic rule.

What is a linguistic rule?

Linguistic rules are often compared to mathematical equations or commands in a programming language:

(4 x 3) + 5 = 17<table border="0" cellspacing=5 cellpadding=5>

slide15

Rules

phonological rule /t/ → [th] / #_

phrase structure rule NP → DET (ADJ) N

semantic rule "x [Student(x) -> Talks(x)]

morphological rule V + [ed] = PAST

sing -> sang

read -> read

sleep -> slept

go -> went

ring-ed

cutt-ed

go-ed

went-ed

Rules + performance factors

slide16

Bybee, Joan and Dan Slobin. 1982.

Rules and schemas in the development and use of the English past tense.

Language 58: 265-289

bybee and slobin 1982
Bybee and Slobin 1982

The overgeneralization rate is determined by two factors:

(1) Frequency

(2) Phonetic form (=similarity)

bybee and slobin 198218
Bybee and Slobin 1982

Hypotheses:

(1) Infrequent irregular verbs will be regularized more often than frequent irregular verbs.

(2) Irregular verbs that are phonetically similar to

regular verbs are regularized less frequently than irregular verbs that are phonetically different from regular verbs.

bybee and slobin 198219
Bybee and Slobin 1982

Children (1,5-5,0)

Spontaneous production data

This is a girl who knows how to __ .

She is __ing.

She did the same thing yesterday.

What did she do yesterday?

Yesterday she __ .

bybee and slobin 198220
Bybee and Slobin 1982

School children (8,9-10,1)

When I get a ballon, I always blow it up.

Yesterday I __ .

Adults

Elicitation of past tense forms under time pressure: 90 irregular verbs and 270 regular verbs

bybee and slobin 198221
Bybee and Slobin 1982

Infrequent verbs were more often regularized than infrequent ones.

Since frequent verbs are deeply entrenched in memory, they are less likely to change.

bybee and slobin 198222
Bybee and Slobin 1982

Irregular verbs that are phonetically similar to regular verbs are less frequently regularized than irregular verbs that are phonetically different from regular verbs.

bybee and slobin 198223
Bybee and Slobin 1982

1. Verbs that do not change at all: beat-beat, cut-cut

2. Verbs that change a final [d] to [t]: send-sent, build-built

3. Verbs that change the stem vowel and end in [t/d]: bite-bit, find-found

4. Verbs that change the stem vowel and a final [d] to [t]: feel-felt, lose-lost

5. Verbs that change the stem vowel, delete a final C, and add [t]: bring-brought

6. Verbs that change [I] to [{] or [ö]: sing-sang, sting-stung

7. Verbs that change the stem vowel in other ways: give-gave, break-broke

8. Verbs that change a final diphthong: blow-blew, fly-flew

bybee and slobin 198225
Bybee and Slobin 1982
  • Addition of an alveolar plosive [t/d] in the past
  • The occurrence of an alveolar plosive [t/d] in the past and present
  • The occurrence of a stem vowel change
bybee and slobin 198229
Bybee and Slobin 1982
  • Type 1. Verbs that form the past tense by a changing stem vowel and the addition of [t/d].
  • Type 2. Verbs that end in both present and past in an alveolar plosive [t/d].
  • Type 3. Verbs that form the past tense by a changing stem vowel and do not end in [t/d].
bybee and slobin 198233
Bybee and Slobin 1982

Why are type 1 verbs less frequently regularized than the two other types of verbs?

walk

walked

bybee and slobin 198234
Bybee and Slobin 1982

Why are type 1 verbs less frequently regularized than the two other types of verbs?

walk

feel

walked

felt

bybee and slobin 198235
Bybee and Slobin 1982

Why are type 2 verbs less often regularized than type 3 verbs?

walk

walked

bybee and slobin 198236
Bybee and Slobin 1982

Why are type 2 verbs less often regularized than type 3 verbs?

walk

find

walked

found

bybee and slobin 198237
Bybee and Slobin 1982

Why are type 2 verbs less often regularized than type 3 verbs?

walk

sing

walked

sang

bybee and slobin 198238
Bybee and Slobin 1982

Why are type 2 verbs less often regularized than type 3 verbs?

walk

sing

walked

sanged

bybee and slobin 198239
Bybee and Slobin 1982

More than 80% of verbs such as see, fly, blow were regularized. Why?

bybee and slobin 198240
Bybee and Slobin 1982

Matching problem

“The phonological clue which the child can use in matching base with past is the consonantal structure of the verb. … Some verbs offer more consonantal structure than others, and would therefore be easier to master.” (277)

slide41

Bybee, Joan and Carol L. Modor. 1983.

Morphological classes as natural categories.

Language 59: 251-270.

slide42

Bybee and Modor 1983

/n/ spin spun/Î/ cling clungfling flung* sling slung* sting stung* string strung* swing swung wring wrung hang hung*/Îk/ slink slunk/k/ stick stuck strike struck*/g/ dig dug*

[ö]-class

slide43

Bybee and Modor 1983

/m/ swim swam swum come came come/n/ begin began begun run ran run/Î/ ring rang rung* sing sang sung spring sprang sprung/Îk/ drink drank drunk shrink shrank shrunksink sank sunk stink stank stunk

[æ]-class

slide44

Bybee and Modor 1983

Subjects: adult speakersItems: 93 nonce words 16 real verbsTechnique: Elicitation of past tense under time pressure

slide45

Bybee and Modor 1983

Examples: sking strin flink streak meek

skung

skinged

strun

strinned

flinked

flunk

streaked

struck

meeked

muck

slide46

Bybee and Modor 1983

  • Stem vowel
  • Initial consonant cluster
  • Final consonant cluster
slide47

Bybee and Modor 1983

Stem vowel:Verbs including [I] are more likely to form irregular past tense forms /like sing-sang) than verbs including other stem vowels.

flink flunk

gleak gloke

slide48

Bybee and Modor 1983

Initial consonants + [I] stem vowel

slide49

Bybee and Modor 1983

Final consonants + [I] stem vowel

slide51

Bybee and Modor 1983

[st] [ö] [Î(g/k)]

string

[xxxx]

slide52

Bybee and Modor 1983

“Membership in morphological classes is not a matter of strict presence or absence of features, but rather of similarity to a prototype, which may be defined on a number of features.” (Bybee and Modor 1983: 263)

exemplar theory view55
Exemplar theory/view

Class 6

Class 5

attractor

exemplar theory view56
Exemplar theory/view

Class 6

Class 5

attractor

slide57

Bybee and Modor 1983

stö[Î(g/k)]

xxx(@)d

sking

strin

cling

streak

bing

tip

kiss

like

slide58

Pinker 1999

Is the regular paste tense a schema (attractor)or does it involve a different mechanims (e.g. a rule)?

The dual mechanisms account:

Words (=schemas) + Rules (=operations over formal categories)

slide59

Bybee and Modor 1983

stö[Î(g/k)]

{[Î(g/k)]

-(@)d

slide60

Bybee and Modor 1983

sking

stö[Î(g/k)]

{[Î(g/k)]

-(@)d

slide61

Bybee and Modor 1983

sking

stö[Î(g/k)]

flink

{[Î(g/k)]

-(@)d

slide62

Bybee and Modor 1983

sking

stö[Î(g/k)]

flink

{[Î(g/k)]

strin

-(@)d

slide63

Bybee and Modor 1983

sking

stö[Î(g/k)]

flink

{[Î(g/k)]

strin

-(@)d

meek

bybee 1995
Bybee 1995
  • The degree of phonetic similarity
  • The number of types that constitute an attractor: The more types are subsumed by an attractor the stronger its force
slide65

Connectionism

Rumelhart, D.E. and J.L. McClelland. 1986. On learning the past tense of English verbs. In David E. Rumelhart and James L. McClelland (eds.), Parallel Distributed Processing. Explanation in Microstructures of Cognition,Vol. II, 216-271. Cambridge: MIT Press.

slide66

Connectionism

Output

Hidden Nodes

Input

slide67

Connectionism

Output

Hidden Nodes

Input

slide68

Bybee and Modor 1983

If the human mind works like a digital computerlinguistic categories are stable entities with clear-cut boundaries, and linguistic productivity is based on (mathematical) rules.

But if the human mind works like a connectionist network linguistic categories are emergent entities with fluid boundaries, and linguistic productivity is based on associations (or analogy).

slide69

Connectionism

Elman, J. et al. (1996) Rethinking innateness. MIT Press.