A minimalist model of code‐switching - Purdue University

Quadros,
Lillo‐Mar/n,
&
Chen
Pichler


Two
Languages
But
One
Computa2on:
 Code‐Blending
in
Bimodal
Bilingual
 Development
 Ronice
Müller
de
Quadros
 Universidade
Federal
de
SC


TISLR
10


ACKNOWLEDGMENTS
 •  Warm
thanks
to:

 –  bimodal
bilingual
children
and
their
families
 –  research
assistants


Diane
Lillo‐Mar2n


University
of
Connec/cut


Deborah
Chen
Pichler
 Gallaudet
University


TISLR
2010

 Purdue
University


INTRODUCTION
 Intermodality


THEORETICAL
FRAMEWORK
 •  One
Computa/on

 –  Lillo‐Mar/n,
Quadros,
Koulidobrova
&
Chen
 Pichler
(2009)


•  Financial
support
from:
 –  Award
Number
R01DC009263
from
the
Na/onal
Ins/tutes
of
Health
 (Na/onal
Ins/tute
on
Deafness
and
Other
Communica/on
Disorders).
 The
content
is
solely
the
responsibility
of
the
authors
and
does
not
 necessarily
represent
the
official
views
of
the
NIDCD
or
the
NIH.

 –  The
Gallaudet
Research
Ins/tute.
 –  CNPq
(Brazilian
Na/onal
Council
of
Technological
and
Scien/fic
 Development)
Grant
#200031/2009‐0
and
#470111/2007‐0.


INTRODUCTION
 •  Studies
of
intermodal
language
development
 can
help
us
becer
understand
the
architecture
 of
the
human
capacity
for
language.

 •  There
is
licle
conflict
between
the
ar/culatory
 mechanisms
of
signed
and
spoken
languages,
 so
it
is
an
excellent
popula/on
in
which
to
test
 ques/ons
of
language
design.


A
minimalist
model

 of
code‐switching
 MacSwan
(2000,
2005)
 Code‐switching
can
be
accounted
for
using
only
the
mechanisms
 needed
to
describe
monolingual
competence


•  MacSwan’s
(2000,
2005)
Minimalist
Model
of
 Code‐Switching
 •  Plus
concepts
from
Distributed
Morphology
 (Halle
&
Marantz
1993,
Idsardi
&
Raimy
2010,
 Siddiqi
2010)
–
cf.
Liceras
et
al.
2005
 MacSwan’s
model
as
illustrated
by
Cantone
&
Müller
(2005)


1


Quadros,
Lillo‐Mar/n,
&
Chen
Pichler


TISLR
10


Distributed
Morphology


One
Computa/on


Important
Notes:
 • In
the
first
steps,
there
are
only
abstract
hierarchical
 features
and
roots
with
no
phonological
material
(no
 language
specifica/on).
 • At
VI,
elements
from
either
language
can
be
inserted
as
long
 as
the
Vocabulary
Items
match
(do
not
conflict)
in
features
 (may
lead
to
code‐switching
or
cross‐linguis/c
influence).

 • Elements
from
both
languages
may
be
inserted
if
they
do
 not
compete
for
ar/cula/on
(code‐blending).


BINATIONAL
STUDY
OF
BIMODAL

 BILINGUAL
LANGUAGE
ACQUISITION


Predic/ons
 •  One
proposi/on
may
be
expressed
in
either
or
 both
modali/es
 •  Bilinguals
will
not
produce
two
different
 ucerances
simultaneously
–
i.e.,
will

 
not
produce:
 –  One
proposi/on
in
sign
while
two
are
produced
in
 speech
(or
vice‐versa)
 –  One
proposi/on
in
sign
while
a
different
one
is
 produced
in
speech
(or
vice‐versa)


Data
analyzed
for
the
current
presenta/on
 Lang’s


Igor
 Ben


Libras
/
 BP
 ASL
/
AE


Lex


ASL
/
AE


Tom


ASL
/
AE


Age
 Range
 2;01
–

 2;11
 2;01
– 2;06
 3;03
–
 3;09
 2;04
–
 2;07


Sess’ns


–  Brazilian
Sign
Language
(Libras)
and
Brazilian
 Portuguese
(BP)
 –  American
Sign
Language
(ASL)
and
English
(E)


Bimodality
under

 One
Computa/on


Par/cipants
 Name


We
examine
the
development
of
a
sign
language
 and
a
spoken
language
in
two
language
pairs:


10


#
Coded
 UI’s
 3610


2


994


2


608


2


398


•  Modality
 – Speech
 – Sign
 – Bimodal
 • Bimodal
Types
 • Bimodal
Overlap
 • Bimodal
Redundancy


All
par/cipants
have
at
least
one
Deaf
parent
and
rela/vely
equal
 exposure
to
both
sign
and
spoken
languages.


2


Quadros,
Lillo‐Mar/n,
&
Chen
Pichler


TISLR
10


Modality
 Speech
Target


Speech
Target


Sign
Target


1.00


Bimodal
Types


Sign
Target


1.00


0.90


0.90


0.80


0.80


0.70


Igor_2;01


0.60


Igor_2;02


0.60


0.50


Igor_2;07


0.50


Igor_2;03


0.40


Igor_2;09


0.40


Igor_2;08


0.30


Igor_2;10


0.20


Igor_2;11


0.10
 0.00


0.70


0.30


Igor_2;09


0.20
 0.10
 0.00


Speech


Sign


Bimodal


Speech


Sign


Bimodal


1.00
 0.90
 0.80
 0.70


BEN_02;01


0.60


TOM_02;04


0.50


BEN_02;06


0.40


TOM_02;07


0.30


LEX_03;03


0.20


LEX_03;09


0.10
 0.00
 Speech


Sign


Bimodal


Bimodal
Overlap


Bimodal
Overlap
 Speech
Target


Sign
Target


1.00


Full


0.90
 0.80
 0.70


Igor_2;01


0.60


Par/al
Included


Igor_2;02


0.50


Igor_2;07


0.40


Igor_2;09


0.30


Mul/
Included


0.20


Igor_2;10


0.10


Igor_2;11


0.00


Igor_2;03
 Igor_2;08
 Igor_2;09


Full
 Full


Par/al
Mismatch


1.00
 0.90
 0.80
 0.70
 0.60
 0.50
 0.40
 0.30
 0.20
 0.10
 0.00


Par/al
 included


Mul/
 included


Par/al
 mismatch


Mul/
 mismatch


Par/al
 Mul/
 Par/al
 Mul/
 included
 included
 mismatch
 mismatch


1.00
 0.90
 0.80
 0.70


Mul/
Mismatch


BEN_02;01


0.60


TOM_02;04


0.50


BEN_02;06


0.40


TOM_02;07


0.30


LEX_03;03


0.20


LEX_03;09


0.10
 0.00
 Full


Bimodal
Redundancy
 Speech
Target


Par/al
 included


Mul/
 included


Par/al
 Mul/
 mismatch
 mismatch


Poten/al
Counterexamples
–
1




Sign
Target


1.00


1.00


•  Timing
overlap
–
Mul/s


0.90


0.90


0.80


0.80


0.70


0.70


Igor_2;01


0.60


Igor_2;02


0.50


Igor_2;07


0.40


Igor_2;09


0.30


Igor_2;10


0.20


0.20


Igor_2;11


0.10


0.10


0.60


Igor_2;03


0.50


Igor_2;08


0.40


Igor_2;09


0.30


Igor
(2;10)


0.00


0.00


Redundant
 Redundant


Not
redundant


Not
redundant


1.00
 0.90
 0.80
 0.70


BEN_02;01


0.60


TOM_02;04


0.50


BEN_02;06


0.40


TOM_02;07


0.30


LEX_03;03


0.20


LEX_03;09


0.10
 0.00
 Redundant


Not
redundant


3


Quadros,
Lillo‐Mar/n,
&
Chen
Pichler


Lengthening


TISLR
10


Poten/al
Counterexamples
–
2



•  Holding
or
repea/ng
of
the
sign
or
word
 •  Used
as
a
conversa/onal
strategy


•  Timing
overlap
–
Mismatches


–  Holding
acen/on
 –  Maintaining
the
topic
 –  Cohesion
across
ucerances
 –  Repairs
 •  (Bennec‐Kastor
1994;
Huang
2010)


Ben
(2;01)


Coordina/on
 •  Children
are
s/ll
developing
the
ability
to
 coordinate
well
manual
and
vocal
outputs
 •  Repe//on
is
used
to
repair
the
ill‐coordinated
 /ming


Poten/al
Counterexamples
–
3


 •  Non‐redundancy
 Ben
(2;01)


Igor
(2;07)


Ben
(2;01)


One
Proposi/on
 •  According
to
our
model,
these
are
not
 counterexamples
as
long
as
combined
they
 express
one
proposi/on

 –  Look,
she’s
sick
 –  This
one
is
black.
 –  I
want
that
toy.


CONCLUSIONS
 •  Mul/ple
kinds
of
blending
are
possible
with
 mul/ple
ar/culators.
 •  Our
model,
incorpora/ng
MacSwan’s
 proposals
for
code‐switching
and
concepts
 from
Distributed
Morphology,
can
capture
 these
possibili/es.


4


Quadros,
Lillo‐Mar/n,
&
Chen
Pichler


TISLR
10


SELECTED
BIBLIOGRAPHY


CONCLUSION


•  • 


One
proposi/on
is
one
computa/on
with
 intermodal
expression.
 Signed
words


Facial
 expressions


•  •  •  •  • 

Gestures


Spoken
words


•  •  •  • 

One
proposi2on


•  •  •  • 

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T.
(1994)
Repe//on
in
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