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Can we devise a new measure of syntactic complexity for language acquisition?

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Can we devise a new measure of syntactic complexity for language acquisition? Duna ú jv á ros, March 18, 2004 Marijan Palmović Laboratory for Psycholinguistic Research University of Zagreb [email protected] http://public.srce.hr/labpolin/.

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slide1

Can we devise a new measure of syntactic complexity for language acquisition?

Dunaújváros, March 18, 2004

Marijan Palmović

Laboratory for Psycholinguistic Research

University of Zagreb

[email protected]

http://public.srce.hr/labpolin/

slide2

Mean Lenght of Utterance – MLU – a traditional measure

  • Simple and good measure for assessing syntactic development
          • but
          • there are problems in morphologically rich languages
          • -not valid crosslinguistically

In Croatian:

- Does not discriminate between children of various developmental rate?

slide3

Vjeran

Antonija

Marina

Croatian corpus (CHILDES): MLU in morphemes

slide4

Vjeran

Antonija

Marina

Croatian corpus (CHILDES): MLU in words

slide5

Various measures for assessing lexical development 1

Type/token ratio (TTR)

  • Generally:
  • Sensible to the size of the file:
  • - larger the file, smaller the TTR
  • -- questionable application in morphologically rich languages
  • Specifically, for Croatian:
  • Not an automatized measure
  • - does not reflect lexical complexity
  • -- ratio always around 1
slide6

Various measures for assessing lexical development 2

  • Number of different words in a standard number of utterances
  • - longer the sentences (and therefore MLU), higher the NDW.

NDW – Number of Different Words

Fixing the number of tokens, not utterances

VOCD: a smarter TTR

- Accounts for the file size

-- takes randomly chosen samples of text

slide7

RRG

  • Role and Reference Grammar
  • Van Valin, LaPolla, 1997, Syntax
slide9

Aktionsart:

  • State
  • Achievement
  • Accomplishment
  • Activity
  • Active accomplishment

+

Causative counterparts

-causative state, causative achievement…

The ice melted. Hot water melted the ice.

Accomplishmentcausative accomplishment

slide10

Verb class Logical structure

State predicate’ (x) or (x,y)

Activity do’ (x, [predicate’ (x) or (x,y)])

Achievement INGR predicate’ (x) or (x,y)

Accomplishment BECOME predicate’ (x) or (x,y)

Lexical representation for the basic Aktionsart classes:

(Van Valin, LaPolla, 1997)

John ate the fish. do’ (John, [eat’ (John, fish)])

Macroroles actor undergoer

slide11

SENTENCE

CLAUSE

CORE

NUCLEUS

PRED

PERIPHERY

ARG

ARG

ADV

NP V NP

John ate the fish yesterday

U

A

do’ (John, [eat’ (John, fish)])

slide12

Antonija

(CHILDES)

Table representing the number of different verb classes

- the first step

slide13

Antonija, 1;9:

*ANT: Ja idem tebi.

%Eng: I am going to you.

*ANT: Ja ću ovo držati.

%Eng: I will hold this.

*ANT: Neću tebi dati olovku.

%Eng: I will not give you the pencil.

slide16

nuclear clausal

cosubordination coordination

strongest weakest

connection connection

Type type

Interclausal Relations Hierarchy - IRH

slide17

CL COO

9

Attach points to different juncture and nexus types…

…to modify the scale obtained from points given for logical form variety

CL SUB

8

CL COSUB

7

CORE COO

6

CORE SUB

5

CORE COSUB

4

NUC COO

3

NUC SUB

2

NUC COSUB

1

slide18

An example:

Strongest connection: nuclear cosubordination

English examples:

John pushed open the door.

Vince wiped the table clean.

Prediction:

-should be acquired first!

slide19

But in Croatian, these sentences are translated differently:

John je gurnuo vrata i otvorio ih.

Vinko je očistio stol.

slide20

The question about the acquisition of complex sentences is reduced to the question about the child’s ability to learn IRH with the stronger connection ocurring first.

  • A child can deduce other grammatical properties of complex sentences, for example, the ones regarding the operators of tense and aspect.
  • Child starts to use clause linkage constructions before mastering the total range of constructions and operators possible in simple sentences.
  • e.g. Hocu piti cajeka. ‘I want to drink tea.’
  • Modify our scale with IRH (add 1 - 9 points)
slide21

verb + verb in infinitive

in the purposive construction

Examples:

Antonija, 1;7: two word sentences, e.g.Hocem ovo. ‘Want this.’ 5+0

Antonija, 1;9 core cosubordination:Idemo pjevati! ‘Let’s sing!’ 4+5

Antonija, 1;10: clausal coordination:

Nis-am pjev-a-la, nego ja s-am pak-a-la.

Be_not-1SG:PRES sing-5-PART:F but I be-1SG:PRES cry-5-PART:F

\'I was not singing, but I was crying.\'

4+9

slide22

Comparison with the MLU

Antonija, 1;7: two word sentences – 5:

MLU (words) = 1,57

MLU (morphemes) = 2,29

Antonija, 1;9 core cosubordination – 9:

MLU (words) = 2,43

MLU (morphemes) = 3,53

Antonija, 1;10: clausal coordination – 13:

MLU (words) = 2,19

MLU (morphemes) = 3,43

slide23

Problems:

  • It is not easy to apply – it is not an automatic measure
  • Selection of verb classes can be problematic due to the imperfective – perfective oppositions of verbs
  • Questionable predictivity regarding the complex sentences: children like to add sentences with conjection i ‘and’.
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