Erin GrantDepartment of Computer Science

University of Toronto

Gender differences in languageproduction and child-directed

speech

ComputationalLinguistics Cognitive

Science

ArtificialIntelligence

TheoreticalLinguistics

Psycho-linguistics

NaturalLanguageProcessing Human-

computerInteraction

MachineLearning

Machinetranslation

What is theintersection

betweencomputer science

andnatural language?

Computationalmodelling

of languageacquisition

Why is thisan interesting

problem?

How cancomputer

science help?

Differences between female and male speech

Differences between female and male speech

Some typical examples:

word frequency

male speech female speechexpletives diminutives

assertions vs. hedges

male speech female speechThat is . This is , isn’t it?

politeness register

male speech female speechdirect requests modals: “could”, “would” && commands politeness markers: “please”

We see systematic differences in the language that childrenproduce when they are young.

“Language development is a domain in which genderdifferences are already well established. . . the [difference] inverbal ability is one of the few gender differences considered tobe robust.” 1

1Lovas, Gretchen. 2011. “Gender and Patterns of Language Development in Mother-Toddler and

Father-Toddler Dyads.” First Language 31 (1): 83-108.

complexity

male speech female speechsmaller vocabulary2 greater syntactic complexity3

2Huttenlocher, Janellen, Wendy Haight, Anthony Bryk, Michael Seltzer, and Thomas Lyons. 1991. “Early

Vocabulary Growth: Relation to Language Input and Gender.” Developmental Psychology 27 (2): 236-248.3

Bornstein, Marc H., Chun-Shin Hahn, and O. Maurice Haynes. “Specific and general language performanceacross early childhood: Stability and gender considerations.” First Language 24, no. 3 (2004): 267-304.

frequency of abstractions4

male speech female speechabstract concrete

4Newman, Matthew L., Carla J. Groom, Lori D. Handelman, and James W. Pennebaker. “Gender differences

in language use: An analysis of 14,000 text samples.” Discourse Processes 45, no. 3 (2008): 211-236.

function: what is the goal of the speech act?56

male speech female speechinstrumental end-in-itselfdeclarative social

5Herring, S. C. (1993). “Gender and democracy in computer-mediated communication.” Electronic Journal

of Communication, 3(2).6

Pennebaker, J. W., Mehl, M. R., & Niederhoffer, K. (2003). “Psychological aspects of natural language use:Our words, our selves.” Annual Review of Psychology, 54, 547577.

Our hypothesis:

The difference can be attributed to the language that thechild is exposed to during the acquisition phase.

Our prediction:

There will be variation in child-directed speech betweenmale and female groups.

The data we are working with. . .

Childes

663,239 utterances

3,206,502 words

We divide the CDS data into four groups:

male speaker to female child female speaker to female childmale speaker to male child female speaker to male child

Can we detect variation between the groups?

Measures

I Word-level measures

I lexical content of thewords:

I emotivityI concreteness

I word frequency

I Phrase-level measures

I Context-level measures

“I wonder whether the teacherwill get mad at me.”

Iself-reference

wondercognitive process; abstraction

whetheruncertainty theteacherreference to school will getmademotive language: anger atmeself-reference.

Measures

I Word-level measures

I Phrase-level measures

I type-to-token ratioI structural frequenciesI mean

length-of-utterance(MLU)

I Context-level measures

“Let’s try to be quiet.”

let us try to be quiet .

ROOT

COMP

SUBJ

XCOMP

XSUBJ

AUX

COP

Measures

I Word-level measures

I Phrase-level measures

I Context-level measures

I topic and surroundingcontext

I function of the speechact

Preliminary results

I MLU (mean length-of-utterance) is higher in speechdirected towards male children

I word type-to-token ratio is higher in speech directedtowards female children

Over the course of the summer. . .

We will:

I determine a method to test the statistical significance ofthese results.

I develop new measures to analyse potential differences.

I find out if our prediction is accurate!

I apply significant features to create a gender classificationalgorithm that can be used on arbitrary text.