Introduction

Corpus, Tools and Method

Three analyses

Reproducible Identification of Pragmatic
Universalia in CHILDES Transcripts
GNU meets OpenScience

Daniel Devatman Hromada123
daniel@wizzion.com
1 Université Paris 8 / Lumières
École Doctorale Cognition, Langage, Interaction
Laboratoire Cognition Humaine et Artificielle
2 Slovak University of Technology
Faculty of Electronic Engineering and Informatics
Department of Robotics and Cybernetics
3 Universität der Künste
Fakultät der Gestaltung, Berlin

Conclusion

Introduction

Corpus, Tools and Method

Table of Contents

1

Introduction
Psycholinguistics
Reproducibility
Universalia

2

Corpus, Tools and Method

3

Three analyses

4

Conclusion

Three analyses

Conclusion

Introduction

Corpus, Tools and Method

Three analyses

Conclusion

Developmental Psycholinguistics
DP
Is a science which uses experimental methods of developmental
psychology in order to study acquisition, learning and development
of linguistic structures and processes in human children.
Multiple epistemological and methodological problems include:
1

child’s behaviour is often very instable

2

the very fact of being subjected to experiment impact child’s
responses

3

the invasivity problem

These problems do not exist when researcher decides to observe
instead of experiment!

Introduction

Corpus, Tools and Method

Three analyses

Conclusion

Reproducibility

The Hallmark Principle

Reproducibility
”Non-reproducible single occurrences are of no significance to
science” (Popper, 1992)
Experimentator-independent reproducibility can be attained iff:
1

all experimentators use the same dataset

2

use the same (or least very similiar) set of tools

3

the first experimentator faithfully protocols the usage of such
tools

4

other experimentators follow the protocol

5

analysis is deterministic

Introduction

Corpus, Tools and Method

Three analyses

Conclusion

Universalia

Pragmatic and Ontogenetic Universalia
Linguistic Universal
A pattern that occurs systematically across natural languages.
Most common lists of universals, like those of Greenberg (1963),
concern syntax, morphology or semantics.
Pragmatic Universal
A L.U. related to pragmatic (extralinguistic context, deictics, etc.)
facet of linguistic communication.
Ontogenetic Universalia
Introduce the temporal dimension (age).

Introduction

Corpus, Tools and Method

Table of Contents

1

Introduction

2

Corpus, Tools and Method
Corpus
Tools
Method

3

Three analyses

4

Conclusion

Three analyses

Conclusion

Introduction

Corpus, Tools and Method

Three analyses

Corpus

CHILDES
CHILDES
Child Language Data Exchange System (MacWhinney&Snow, 1985)
http://childes.psy.cmu.edu/data
http://wizzion.com/CHILDES/ (mirror from 6th Feb 2016)

1

more than 50 years of tradition

2

cca 30000 transcripts

3

more than 1.5 GigaBytes of mostly textual data

4

at least 26 languages, dialects or language combinations

5

major terran language-groups (indo-european, ugro-finic,
semitic, altaic, east-asian, south-asian) represented

6

Creative Commons BY-NC-SA licence

Conclusion

Introduction

Corpus, Tools and Method

Three analyses

Conclusion

Corpus

CHAT format
CHAT system provides a standardized format for producing computerized
transcripts of face-to-face conversational interactions. (MacWhinney,
2016; http://childes.talkbank.org/manuals/chat.pdf).

@Begin
@Languages:
eng
@Participants: CHI Eve Target_Child , MOT Sue Mother , FAT David Father
@ID:
eng|Brown|CHI|1;6.|female|||Target_Child|||
@ID:
eng|Brown|MOT|||||Mother|||
@ID:
eng|Brown|FAT|||||Father|||
@ID:
eng|Brown|RIC|||||Investigator|||
@ID:
eng|Brown|COL|||||Investigator|||
@Date: 29-OCT-1962
*MOT:
one two three four .
%mor:
det:num|one det:num|two det:num|three det:num|four .
%act:
tests tape recorder
*CHI:
one two three . [+ IMIT]

Introduction

Corpus, Tools and Method

Three analyses

Conclusion

Tools

GNU + PERL + R
The idea is to perform the analysis with solely publicly-available
open-source command-line tools.
GPR combo
GNU: grep, sort, uniq, sed, wc (runs in bash and connected
through pipes)
PERL: regular expressions are part of language syntax
R: vectors, matrices, plotting
First command
wget -P CHILDES -e robots=off –no-parent –accept ’.cha’ -r
http://wizzion.com/childes/CHILDES flat

Introduction

Corpus, Tools and Method

Three analyses

Method

Pre-processing
Populate filenames with age information
mkdir aged; grep -P ’\|\d;\d’ *| grep Child |
perl -n -e ’chomp; ‘cp $1 aged/$2-$3-$1‘
if /^(.*?):.*0?(\d+);0?(\d+)/;’ ; rm *.cha
Remove noise
perl -ni -e ’print
if $_!~/^\*(MOT|CHI):\t(xxx|www) ?\./’ aged/*
Extract Child and Motherese utterances
mkdir CHI; cp aged/* CHI; sed -i ’/\*CHI/! d’ CHI/*;
mkdir MOT; cp aged/* MOT; sed -i ’/\*MOT/! d’ MOT/*;
Yields
5 833 656 CHI utterances contained in 29180 transcripts
3 798 005 MOT utterances contained in 13590 transcripts

Conclusion

Introduction

Corpus, Tools and Method

Three analyses

Conclusion

Method

Metrics

Main metrics: Probability PX that signifiant X shall occur in the
utterance.
PX = FX /Nutterances
where FX is the absolute number of occurences of X in CHILDES
section and the normalization factor Nutterances denotes the number
of utterances of the CHILDES section.

Probability values are mutually comparable.

Introduction

Corpus, Tools and Method

Table of Contents

1

Introduction

2

Corpus, Tools and Method

3

Three analyses
1st analysis: Laughing
2nd analysis: Second Person Singular
3rd analysis: First Person Singular

4

Conclusion

Three analyses

Conclusion

Introduction

Corpus, Tools and Method

Three analyses

Conclusion

1st analysis: Laughing

Laughing
Objective
Verify whether observed tendency (Hromada, 2016, Conceptual
Foundations) of mothers to laugh less is in interaction with older
toddlers is specific to English, or whether it is a
culture-independent invariant.
Both &=laughs and =!laughing tokens are used by diverse CHILDES
transcribers, so we simply use for occurences of laugh token.
grep laugh MOT/*French*|grep -o -P ’\-French\-.+\-’|
sort|uniq -c;grep laugh MOT/*Farsi*|grep -o -P ’\-Farsi\-.+\-’|
sort|uniq -c;grep laugh MOT/*Japanese*|grep -o -P ’\-Japanese\-.+\-’
|sort|uniq -c;grep laugh MOT/*Chinese*
|grep -o -P ’\-Chinese\-.+\-’ | sort | uniq -c ;
wc -l MOT/*Eng*|perl -e
’while (<>){s/MOT\///;/(\d+) (\d+-\d+)-/;
$h{$2}+=$1; } for (sort keys %h) {/(\d+)-(\d+)/;
print "$h{$_} $1 $2\n";}’ >MOT.Eng.N

Introduction
1st analysis: Laughing

Plot

Corpus, Tools and Method

Three analyses

Conclusion

Introduction

Corpus, Tools and Method

Three analyses

Conclusion

1st analysis: Laughing

Some observations
For english, french and farsi children:
marked decrease of maternal laughing between first and third
year of age (english, french, farsi)
little children laugh more often than their mothers but older
children laugh less frequently than their mothers
significant correlations between MOT and CHI in English
(Pearson’s cor.coeff 0.933, p = 7.886e-05) and in Farsi (corr.
coef. 0.972, p-value=0.02735). Almost significant in French
(p=0.053, cor. coef = 0.947)
In regards to laughing, Indo-European mothers and children seem
to follow different ontogenetic trajectories than their Japanese and
Chinese counterparts
⇒
no culture-independent Universal ?

Introduction

Corpus, Tools and Method

Three analyses

Conclusion

2nd analysis: Second Person Singular

2nd Person. Sg. Pronouns
Language-specific CHILDES sub-corpora are matched by following
Perl-Compatible regular expressions (PCREs):

The absolute frequency FX of cases when PCREX matched is
assessed as usually:
grep -i -P "[\t ]you[’ ]" MOT/*Eng*|
perl -n -e ’/MOT\/(\d+)-(\d+)/;
print "$1 $2\n"’ |uniq -c >exp2.MOT.Eng.F
Subsequently, FX /Nutterances division and plotting are realized in R. (c.f.
http://wizzion.com/code/jadt2016/childes.R for the trivial R-code snippet)

Introduction

Corpus, Tools and Method

2nd analysis: Second Person Singular

Plot

Three analyses

Conclusion

Introduction

Corpus, Tools and Method

Three analyses

Conclusion

2nd analysis: Second Person Singular

Some observations
One can observe, in English
in motherese, ”you” is used in cca every fifth utterance
significant correlation between CHI and MOT time series
(Pearson’s cor. coeff. = 0.768, t = 3.393, df = 8, p-value =
0.009451; Kendall’s tau = 0.6, T = 36, p-value = 0.016671;
Spearman’s rho = 0.733, S = 44, p-value = 0.02117)
One can observe, in all languages
Marked increase in maternal usage of 2nd. p. sg. between 1st
and 4th year of age has been observed in case of all six studied
languages (representing three distinct language groups).
children use 2nd. p. sg. less often than mothers (only
exception: Farsi between 2 and 3)
⇒ ontogenetic Universal ?

Introduction

Corpus, Tools and Method

Three analyses

Conclusion

3rd analysis: First Person Singular

1st Person. Sg. Pronouns
Language-specific CHILDES sub-corpora are matched by following
Perl-Compatible regular expressions (PCREs):

The absolute frequency FX of cases when PCREX matched is
assessed as usually:
grep -i -P "[\t ]I[’ ]" MOT/*Eng*|
perl -n -e ’/MOT\/(\d+)-(\d+)/;
print "$1 $2\n"’ |uniq -c >exp3.MOT.Eng.F
Subsequently, FX /Nutterances division and plotting are realized in R. (c.f.
http://wizzion.com/code/jadt2016/childes.R for the trivial R-code snippet)
Important: focus on ALL transcripts of a given language.

Introduction

Corpus, Tools and Method

3rd analysis: First Person Singular

Plot

Three analyses

Conclusion

Introduction

Corpus, Tools and Method

Three analyses

Conclusion

3rd analysis: First Person Singular

Some observations
ALL: around 3 years of age, children tend to pronounce 1.p.sg
much more frequently than their mothers
ALL: steep decline between 6th and 7th year of age (offset of
”egocentric” stage?)
ENGLISH: significant correlation between usage of mothers
and children
Significant intercultural correlations
french and chinese children (p=0.02474)
english and french children (p=0.002425)
polish and hebrew children (p=0.048)
polish and french children (p=0.048)
⇒ language-independent ontogenetic trajectory of usage of 1.p.sg?

Introduction

Corpus, Tools and Method

Table of Contents

1

Introduction

2

Corpus, Tools and Method

3

Three analyses

4

Conclusion

Three analyses

Conclusion

Introduction

Corpus, Tools and Method

Three analyses

Conclusion

Methodological conclusion
Combination of
command-line (no GUI!)
open-source (for free!)
fast *
deterministic
utils (grep, uniq, ...) and languages (PERL, R) yields a 100%
reproducible methodology for very little cost.
Experimental protocol automatically stored in .history (or
.bash history) and .RHistory files: no need to reinvent the wheel!
* 3rd analysis executed on one sole core of 3.2 Ghz PC with 8GB RAM and
CHILDES data stored on a SSD disk was over in less than 15 seconds

Introduction

Corpus, Tools and Method

Three analyses

Conclusion

Epistemological conclusion

Developmental Psycholinguistics + Natural Language Processing
+ Big Data + OpenScience
=
la textometrie psycholinguistique

Manifest:
to perform state-of-the-art research without expensive tools
and apparati
to study ontogeny of soul and language in a non-invasive
fashion
to share all that can be shared

Introduction

Corpus, Tools and Method

Psycholinguistic conclusion

Piaget eut raison.

Three analyses

Conclusion

Introduction

Corpus, Tools and Method

Three analyses

Merci pour votre attention.
Questions ?

Conclusion