Vsevolod Kapatsinski
Indiana University
Dept. of Linguistics
Cognitive Science Program
Speech Research Laboratory vkapatsi@indiana.edu
http://mypage.iu.edu/~vkapatsi/

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 productoriented rather than source-oriented. A productoriented schema generalizes over forms of a specific category, but does not specify how to derive that category from some other.”
Source oriented: k] sg
 t  i] pl
Productoriented: ‘plurals must end in t  i’

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

(Bybee & Newman 1995)

BLUE RED
{k;g}  {t  ;d  }i 100%
30
{t;d;p;b}
{t;d;p;b}


{t;d;p;b}i
{t;d;p;b}a
25%
8
75%
24
75%
24
25%
8
Two plural suffixes –i and -a
If –i attached to a velar ({k;g}), the velar changes to an alveopalatal
This is velar palatalization

The process:
• k  t  /_i
Productivity:
• p (k  t  i ) / ( p (k  t  i ) + p (k  ki ) )
Coding scheme:
BLUE – velar palatalization applies
RED – velar palatalization fails

• Does the productivity of velar palatalization differ in the BLUE language and the RED language?
• Depends on your model of grammar.

BLUE RED
{k;g}  {t  ;d  }i
{t;d;p;b}  {t;d;p;b}i
{t;d;p;b}  {t;d;p;b}a
25%
8
75%
24
100%
30 /62
75%
24
25%
8

Triggers velar palatalization
Does not compete with anything
Equally supported in both languages
BLUE = RED
BLUE RED
{k;g}  {t  ;d  }i 100%
30
{t;d;p;b}  {t;d;p;b}i
{t;d;p;b}  {t;d;p;b}a
25%
8
75%
24
75%
24
25%
8 e.g., Hale and Reiss 2008, Plag 2003

Triggers velar palatalization
BLUE
BLUE = RED
RED
{k;g}  {t  ;d  }i 100%
30
{t;d;p;b}
{t;d;p;b}


{t;d;p;b}i
{t;d;p;b}a
25%
8
75%
24
75%
24
25%
8
Bybee & Slobin 1982, Bybee & Moder 1983, Bybee 2001

Triggers velar palatalization
/ki/ less expected in the blue language
 its absence is less notable
BLUE < RED
BLUE RED
{k;g}  {t  ;d  }i
*ki
{t;d;p;b}  {t;d;p;b}i
100%
30
0
Ci
{t;d;p;b}  {t;d;p;b}a
25%
8
38
75%
24
75%
24
54
25%
8

Triggers velar palatalization
Competes with
Competition stronger in red
BLUE > RED
BLUE RED
{k;g}  {t  ;d  }i 100%
30
C
C


Ci
Ca
25%
8
75%
24
Iff the choice between the rules is stochastic.
75%
24
25%
8
Albright & Hayes 2003

Triggers velar palatalization
More reliable in blue
BLUE > RED
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
Aslin et al. 1998

BLUE RED

100%
30 Non-competing rules
*
Simple positive product-oriented
Negative product-oriented
Competing weighted rules
Conditional product-oriented
BLUE RED

C  Ci
{p;b;t;d}
C  Ca
{p;b;t;d}
{k;g}  {t  ;d  }i
BLUE RED
25%
8
75%
24
100%
30
75%
24
25%
8
Albright & Hayes 2003

***
Competing weighted rules
ANCOVA:
This correlation is significant
F(1,27)=14.23, p<.001
, while Language is not,
F(1,27)=.082, p>.5) .
The predicted explanatory variable accounts for all the variance in velar palatalization rate attributable to the artificial language
22

Conditional product-oriented generalizations
{k;g}  {t  ;d  } | i
{t  ;d  }  {t  ;d  } | i
{t;d;p;b}  {t;d;p;b} | i
{t;d;p;b}  {t;d;p;b} | a
BLUE
Support vel.pal
8/38
1
RED
Support vel.pal
24/54
1

{k;g}  {t  ;d  }i
{t  ;d  }  {t  ;d  }i
C  Ci
C  Ca
Competing weighted rules
BLUE RED
Oppose vel.pal
75%
24
100%
30
Oppose vel.pal
25%
8

Competing weighted rules r(33) = -.49, p=.003

The addition of t   t  i hurts vel.pal
Competing weighted rules
(Conditional) product-oriented t(33)=2.88, p=.007

Something that looks productoriented but isn’t
BLUE RED
Result: All subjects attach
–i rather than –a to singulars ending in {t  ;d ʒ}
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 productoriented schema? ‘Plurals must end in {t  ;dʒ}i’.

Why not?
• 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.

It’s categorization of source forms.
Why more –i with {t  ;d ʒ
} than with {k;g}?
Subjects have a bias against stem changes.
The more a subject attaches –i to velars, the more s/he attaches it to alveopalatals.

Prior experimental evidence for productoriented generalizations
• Frequent output patterns get ‘overused’, being derived from inputs in ways that are not attested in the lexicon, e.g., [v  n] 
[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 [  ]’

• 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 sourceoriented 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

• 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.

χ 2 =28.9, p<.0001
t   t  i k k  t  i repeated as
 ki

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.
35

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.
36

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