• Aucun résultat trouvé

Conceptualization in process: Motion event processing in English and French

N/A
N/A
Protected

Academic year: 2021

Partager "Conceptualization in process: Motion event processing in English and French"

Copied!
2
0
0

Texte intégral

(1)

HAL Id: halshs-01293405

https://halshs.archives-ouvertes.fr/halshs-01293405v2

Submitted on 8 Aug 2016

HAL is a multi-disciplinary open access

archive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Conceptualization in process: Motion event processing in English and French

Helen Engemann, Coralie Vincent, Efstathia Soroli, Maya Hickmann

To cite this version:

Helen Engemann, Coralie Vincent, Efstathia Soroli, Maya Hickmann. Conceptualization in process: Motion event processing in English and French. 3rd AttLis workshop ”The Attentive Listener in the Visual World”, Mar 2016, Potsdam, Germany. �halshs-01293405v2�

(2)

0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1

Path

Manner

Path

Manner

English

French

Non-verbal

Verbal

0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1

Non-verbal

Verbal

English

French

Fig 4. Categorization: Proportions of Manner choices

0 0,2 0,4 0,6 0,8 1 1,2 1,4 1,6 1,8

English

French

s

ec

onds

Non-verbal

Verbal

p < 0.05 main

effect of language

Tobii X120 head-free binocular remote desktop

eye-tracker (120 Hz)

Dynamic AOIs hand-drawn for each stimulus,

allowing precise monitoring of fixations

Conceptualization online:

Processing motion

events

in English and French

Helen Engemann

1

, Coralie Vincent

2

, Efstathia Soroli

3

, Maya Hickmann

2

1

Goethe Universität Frankfurt,

2

Laboratoire Structures Formelles du Langage, CNRS & Université Paris 8,

3

Laboratoire Savoirs, Textes, Langage, CNRS & Université Lille 3

The Attentive Listener in the Visual World (3

rd

AttLis Workshop), 10-11 March 2016, Postdam, Germany

Helen Engemann

Institut für Psycholinguistik &

Didaktik der deutschen Sprache

Goethe Universität Frankfurt

h.engemann@em.uni-frankfurt.de

Contacts

1. Slobin, D. I. (1996). From « thought and language » to « thinking for speaking ». In J. J. Gumperz & S. C. Levinson (ed.), Rethinking linguistic relativity (p. 70-96). Cambridge, UK: Cambridge University Press.

2. Slobin, D. I. (2004). How people move: Discourse effects of linguistic typology. In C. L. Moder & A. Martinovic-Zic (ed.), Discourse across languages and

cultures (p. 195-210). Amsterdam & Philadelphia: John Benjamins Publishing.

3. Choi, S. & Bowerman, M. (1991). Learning to express motion events in English and Korean: The influence of language-specific lexicalization patterns.

Cognition, 41, p. 83–121.

4. Choi, S. & Hattrup, K. (2012). Relative contribution of cognition/perception and language on spatial categorization. Cognitive Science, 36, 102–129. 5. Talmy, L. (2000). Toward a Cognitive Semantics: Typology and Process in Concept Structuring (Vol. 2). Cambridge (Mass.); London: the MIT Press. 6. R Core Team (2015). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.

7. Bates, D., Maechler, M., Bolker, B. & Walker, S. (2015). Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67(1), 1-48.

8. Hanke, M., Halchenko, Y. O., Sederberg, P. B., Hanson, S. J., Haxby, J. V. & Pollmann, S. (2008). PyMVPA: A Python toolbox for classifier-based data

analysis. Poster presented at the 34th conference "Psychology and Brain" (Psychologie und Gehirn 2008).

References

Thinking-for-speaking hypothesis

[1,2]

Language as filter on event construal

Language-specific encoding patterns affect

attention allocation during online speech

processes

Routinely encoded aspects of reality are

more salient to speakers

Effect on children’s conceptual and linguistic

development [3,4]

Introduction

- Categorization: Manner criterion EN > FR

- Memory:

Manner recognition errors FR > EN

- Gaze pattern: Total fixation duration on

Manner-relevant AOI EN > FR

Motion Event Typology

[5]

Participants

Offline measures show effects of condition (NV vs. VE)

Eye movements reveal significant language-specific processing differences, also in non-verbal conditions

Not all cognitive processes affected alike: impact on fixations during categorization, but not memorization

No meaningful results with classification analysis

Future directions: Investigating motion processing in children's development and in bilingual speakers

Discussion & future directions

Hypotheses

Satellite-framing

PATH

: verb

(traverser, monter)

Verb-framing

MANNER

: gerund, adverbial

(en courant)

MANNER

: verb

(run, jump)

jumping

up

monter

(

en sautant

)

PATH

: satellite

(up, down, away)

( )

Research Questions

Q1: Do cross-linguistic differences in motion

expression affect motion event processing?

Q2: Which domains of cognition are affected and

in what condition (verbal and/or non-verbal)?

Q3: Does typology impact children’s linguistic

and conceptual development of motion

representation?

Materials & Procedure

Non-verbal

condition:

Articulatory

suppression

Variant 1 ≠ Manner

Variant 2 ≠ Path

Verbal

condition:

Motion

verbalization

She cycled in

Which one looks most like the target?

Variant 1 = target

Variant 2 ≠ Manner OR Path

Which one did you see before?

Target presentation

Memory: types of recognition error

Fixation duration during viewing for production

Exploratory gaze analysis

[8]

Coralie Vincent and

Maya Hickmann

Laboratoire Structures

Formelles du Langage

CNRS & Université Paris 8

Efstathia Soroli

Laboratoire Savoirs, Textes,

Langage

CNRS & Université Lille 3

efstathia.soroli@univ-lille3.fr

Fig 5. Error types as proportion of total recognition errors

Fig 1. Definition of dynamic zones of interest

Eye-tracking: Dynamic AOIs

---.

predictions\targets 1 2 Summary \ Means:

`--- ---- ---- CHI^2 19.09 p=0.00026

1 32 30 ACC 0.5 2 12 10 ACC% 50

Categorization task

Memory task

Categorization: Manner responses

p < 0.05

effect of condition

Classification using PyMVPA algorithm

Results offline measures

Results eye movements

[6,7]

Fig 2. Total fixation duration (means) on Manner-AOI (Legs)

Fixation duration during categorization

Fig 3. Total fixation duration (means) on Manner-AOI (Legs)

Adults

NV

English

French

NV

English

VE

French

VE

Categorization

22

19

18

19

Memorization

19

20

19

18

Babibo…

Between-subject

design

LANGACROSS-2 was funded by ANR & DFG

http://archive.sfl.cnrs.fr/-LANGACROSS-2-2011-2014-Utterance-.html

Fixation duration memorization:

No sig. differences

p < 0.0001

effect of error type

0 0,2 0,4 0,6 0,8 1 1,2 1,4 1,6 1,8

English

French

s

ec

onds

Production after categorization task

Production before categorization task

p < 0.01

Références

Documents relatifs

We extend current event models to incorporate more aspects of (complex) event processing and demon- strate how streams of structured and heterogeneous event objects, represented

The contribution of this paper is three-fold: 1) it dis- cusses the lack of event-processing support in current APLs and a suitable way of addressing this issue from the

In this workshop, which took 1-2h depending on the school, teachers followed three steps: (1) Working with edCrumble for documenting the LDs implemented at class, adding the

events relevant for logistics from various heterogeneous sources, and (ii) GET Control- ler, which executes and monitors logistics process instances thereby considering events

Expressing and Categorizing Motion in French and English : Verbal and Non-Verbal Cognition across Languages.. International workshop ” Sylex III : Space and motion across languages

Our general research question was, “How do the student's ideas evolve in our teaching sequence on gases?” To follow the student's conceptualization, we will focus on the

In this paper we present CEVICHE, a framework that combines the strengths of complex event processing and dynamic business process adaptation, which allows to respond to the needs

As we have mentioned, we are interested in detecting events, which are emitted when a function, computed over the data of different distributed nodes, has crossed a specific