Experimental evidence for product-oriented generalizations (or not)

Experimental evidence for product-oriented generalizations

(or not)Vsevolod Kapatsinski

Indiana UniversityDept. of Linguistics

Cognitive Science ProgramSpeech Research Laboratory

[email protected]://mypage.iu.edu/~vkapatsi/

mailto:[email protected]

Product-oriented vs. source-oriented generalizations

• Bybee (2001:126)

“Generative rules express source-oriented generalizations. That is, they act on a specific input to change it in well-defined ways into an output of a certain form. Many, if not all, schemas are product-oriented rather than source-oriented. A product-oriented schema generalizes over forms of a specific category, but does not specify how to derive that category from some other.”

Source oriented: k]sg ti]pl

Product-oriented: ‘plurals must end in ti’

Present study

• Given an artificial lexicon and a particular training paradigm what generalizations do the learners extract?

The paradigm(Bybee & Newman 1995)

The artificial languages BLUE RED

{k;g}{t;d}i 100%

30

{t;d;p;b} {t;d;p;b}i 25%

8

75%

24

{t;d;p;b} {t;d;p;b}a

75%

24

25%

8

Two plural suffixes –i and -a

If –i attached to a velar ({k;g}), the velar changes to an alveopalatalThis is velar palatalization

Velar palatalization

The process:

• k t /_i

Productivity:

• p(k ti) / ( p(k ti) + p(kki) )

Coding scheme:BLUE – velar palatalization appliesRED – velar palatalization fails

Research question

• Does the productivity of velar palatalization differ in the BLUE language and the RED language?

• Depends on your model of grammar.

The possible grammars

BLUE RED

{k;g}{t;d}i 100%

30

{t;d;p;b} {t;d;p;b}i 25%

8

75%

24


75%

24

25%

8

/62

Non-competing rules

BLUE RED

{k;g}{t;d}i 100%

30

{t;d;p;b} {t;d;p;b}i 25%

8

75%

24


75%

24

25%

8

Triggers velar palatalizationDoes not compete with anything

Equally supported in both languages

BLUE = RED

e.g., Hale and Reiss 2008, Plag 2003

Simple positive product-oriented generalizations

BLUE RED

{k;g} {t;d}i 100%

30

{t;d;p;b}

{t;d;p;b}i 25%

8

75%

24

{t;d;p;b}

{t;d;p;b}a 75%

24

25%

8

Triggers velar palatalization

BLUE = RED

Equally supported in both languages

Bybee & Slobin 1982, Bybee & Moder 1983, Bybee 2001

Negative product-oriented generalizations

BLUE RED

{k;g} {t;d}i 100%

30

*ki 0

{t;d;p;b}

{t;d;p;b}i 25%

8

75%

24

Ci 38 54

{t;d;p;b}

{t;d;p;b}a 75%

24

25%

8


/ki/ less expected in the blue language its absence is less notable

BLUE < RED

Competing weighted rules

BLUE RED

{k;g}{t;d}i 100%

30

C Ci 25%

8

75%

24

C Ca 75%

24

25%

8


BLUE > RED

Competes withCompetition stronger in red

Albright & Hayes 2003Iff the choice between the rules is stochastic.

Conditional product-oriented generalizations

BLUE RED

{k;g} {t;d} | i 30/38 30/54

{t;d;p;b}

{t;d;p;b} | i 8/38 24/54

{t;d;p;b}

{t;d;p;b} | a 1 1

BLUE > RED


More reliable in blue

Aslin et al. 1998

Result

BLUE RED

Results

*

100%30

BLUE RED

Non-competing rules

Simple positive product-oriented

Negative product-oriented


Conditional product-oriented

Individual subject data


BLUE RED

{k;g}{t;d}i 100%

30

C Ci 25%

8

75%

24

C Ca 75%

24

25%

8Albright & Hayes 2003

{p;b;t;d}

{p;b;t;d}

22

Results***


ANCOVA:This correlation is significantF(1,27)=14.23, p<.001, while Language is not, F(1,27)=.082, p>.5).

The predicted explanatory variableaccounts for all the variancein velar palatalization rateattributable to the artificial language

The competing rules look good.

Can we pit them against (conditional) product-oriented

generalizations directly?

BLUE RED

{k;g} {t;d} | i Support

vel.pal

Support

vel.pal{t;d} {t;d} | i{t;d;p;b}

{t;d;p;b} | i 8/38 24/54

{t;d;p;b}

{t;d;p;b} | a 1 1

Conditional product-oriented generalizations


BLUE RED

{k;g}{t;d}i 100%

30

{t;d}{t;d}i Oppose

vel.pal

Oppose

vel.palC Ci

C Ca 75%

24

25%

8


r(33) = -.49, p=.003

The addition of tti hurts vel.pal

t(33)=2.88, p=.007

Competing weighted rules(Conditional) product-oriented

Something that looks product-oriented but isn’t

Result: All subjects attach –i rather than –a to singulars ending in {t;dʒ}In the Blue Language even more than to singulars ending in {k;g}

H: Because both languages have plurals ending in {t;dʒ}i, not {t;dʒ}a.A product-oriented schema? ‘Plurals must end in {t;dʒ}i’.

BLUE RED

• If – {t;dʒ} {t;dʒ}i because of ‘Plurals must end

in {t;dʒ}i’, and this is the schema that does {k;g} {t;dʒ}i,

• Then– there should be a positive correlation between

rate of {k;g} {t;dʒ}i and rate of {t;dʒ} {t;dʒ}i

• But r=-.03, n.s.

Why not?

It’s categorization of source forms.

The more a subject attaches –i to velars, the more s/he attaches it to alveopalatals.

Why more –iwith {t;dʒ}than with {k;g}?

Subjects havea bias againststem changes.

Prior experimental evidence for product-oriented generalizations

• Frequent output patterns get ‘overused’, being derived from inputs in ways that are not attested in the lexicon, e.g., [vn] [v] (Bybee & Moder, 1983).

(Also see Köpcke 1988, Lobben 1991, Wang and Derwing 1994, Albright and Hayes 2003)

• H: because the subjects have generalized ‘past tense forms must end in []’

An alternative interpretation

• H’: The production of an output primes sublexical chunks occurring in that output.

• Lobben (1991)– “the plurals [that don’t obey the rules but all end in ooCii] are

appearing concentrated and subsequently… and… this is a typical characteristic of all other plural patterns’ (Lobben 1991:173),

– ‘[In this example] the second syllable of the singular is left out in the plural form, which never happens with real nouns… The surrounding… plurals, two preceding and seven following… are trisyllabic [in accordance with source-oriented rules]. This… provides an explanation as to why the plural [in this example], which, if produced according to the rule… , would have four syllables, is made to have three syllables in a very unorthodox way’ (Lobben 1991:182)

• Presupposition: the output is more salient than the input chunks from the output are more likely to persist and be reused than chunks from the input

Are products more salient than sources?

• During training, subjects repeated the word pairs they heard.

• Subjects have a bias against stem changes

If the product is more salient, they should tend to erroneously make the shape of the singular fit the shape of the plural.

If the source is more salient, the plural should fit the singular.

Products are more salient

t ti k ki

k ti repeated as

χ2=28.9, p<.0001

35

In this AGL paradigm (Bybee & Newman 1995),

• Learners extract competing rules

• The outcome of competition is influenced by reliability or type frequency (Albright and Hayes 2003, Pierrehumbert 2006)

• The choice between rules is stochastic

• No evidence for product-oriented generalizations.

Future work: Role of the training paradigm.

Summary

36

Product forms are more salient than source forms. Thus creating a product may prime chunks and patterns that occur in that product for immediate reuse.

This product priming may result in ‘overuse’ of frequent product patterns (found by Bybee & Moder 1983, Koepcke 1988, Lobben 1991, Wang & Derwing 1994, Albright & Hayes, 2003).

If long-lasting, it may also result in the emergence of product-oriented schemas over time.

Summary

ReferencesAlbright, A., and B. Hayes. 2003. Rules vs. analogy in English past tenses: A

computational/experimental study. Cognition, 90, 119-61.Aslin, R. N., J. R. Saffran, & E. L. Newport. 1998. Computation of conditional probability

statistics by 8-month-old infants. Psychological Science, 9, 321-4.Bybee, J. L. 2001. Phonology and language use. CUP.Bybee, J. L., & C. L. Moder. 1983. Morphological classes as natural categories. Language,

59, 251-70.Bybee, J. L., & J. E. Newman. 1995. Are stem changes as natural as affixes? Linguistics, 33,

633-54.Bybee, J. L., & D. I. Slobin. 1982. Rules and schemas in the development and use of the

English past. Language 58: 265-89.Hale, M., & C. Reiss. 2008. The phonological enterprise. OUP.Köpcke, K.-M. 1988. Schemas in German plural formation. Lingua, 74, 303-35.Lobben, M. 1991. Pluralization of Hausa nouns, viewed from psycholinguistic experiments

and child language data. M.Phil Thesis, University of Oslo.Pierrehumbert, J. B. 2006. The statistical basis of an unnatural alternation. In Laboratory

Phonology 8, 81-107. Mouton de Gruyter.Plag, I. 1999. Word formation in English. Mouton de Gruyter.Wang, H. S., & B. L. Derwing. 1994. Some vowel schemas in three English morphological

classes: Experimental evidence. In M. Y. Chen & O. C. L. Tseng, eds. In honor of Professor William S.-Y. Wang: Interdisciplinary studies on language and language change, 561-75. Taipei: Pyramid Press.

Documents

Experimental evidence for product-oriented generalizations (or not)