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1

Act-out paradigm

Demonstrate/explain a novel verb and then ask the kid to act it out

Kid does the action well when an animal does it, but gets it backwards when
the book should be doing it instead of the sheep

Around age 2.5, kids were just above chance
Much better at age 3.5 - English kids were almost perfect
By age 4.5, English speaking generally
got it right

Using the word order of English even though it goes against real world
knowledge

English very rarely uses passive voice in the spoken word

2

Transitive construction

A type of sentence where a verb is related to at least two nouns

Word order
A doer and a done-to

Kids do make these errors - over-generalization

3

Intransitive construction

A type of sentence in which a verb in related to only one noun

The noun is characteristically an agent
In English the noun comes before the verb

The man thinks.

4

Ditransitive construction

A sentence in which a verb is related to at least three nouns

Giver, recipient, given
Word order

5

Verb Island Hypothesis

Akhtar and Tomasello

Children's early language is organized and structured around individual verbs
and other predictive terms

No evidence of abstract grammatical categories

Every verb is an island

20 children, 2.75 and 3.75 years
Children are shown many models of a novel transitive action and told
This is dacking.

Given toys and asked
Make Cookie Monster dack Big Bird.

Both ages could act out familiar verbs
3.75 year olds are really good with the unfamiliar verbs

Kids' knowledge of word order at 2.75 years is still specific to particular
verbs and not generally applied

6

Preferential looking task for verb island hypothesis

Gertner et. al

The duck is gorping the bunny. Find gorping.
Show two pictures.

At what age are kids good at this task?
21 month olds were at 70%

7

"Diary" studies

Researcher is the caregiver
Write down interesting new things children do in a diary

Limitations
‣ Report momentous accomplishments more than mistakes
‣ Who's to say what a momentous event is
‣ Smaller things are not noticed, or are not noticed as important for
months
‣ Only one or two children per study
‣ Only children of a certain socioeconomic class/children of researchers
are studied
‣ Bias - the researcher is coming with specific expectations
(People perceive bias even if it isn't there)
‣ Hard to replicate the circumstances under which a child learned
something

Advantages
‣ Longevity
‣ Outside of artificial lab setting
‣ Caregiver might over interpret, but they will understand their kids better
than a transcriptionist

8

Naturalistic data analysis

Large collections of transcriptions of kids interacting with the primary
caregiver

Recent data sets include recordings of children for an hour or more
everyday from before their second birthday until age four

Video and (transcribed) audio

Limitations
‣ A lot of what kids do does not involve language - hard to get language
development information - need lots of recordings
‣ If you have an hour of dense language, the kids might have been
manipulated by the parents to say things (hard to be natural) - lots of
questions
‣ Sometimes hard to understand the kid (for the transcriptionist) - might
be misinterpreted
The kid copies what the dad says - ‣ he's asking leading questions

Advantages
‣ Objective recording
‣ Not selectively reported
‣ Can have data collected from non-experts' (not researchers') children

9

Pivot grammar

Braine

Two word stage

Pivots and objects

P1 + O - more juice, more milk
O + P2 - juice gone, mommy gone
O + O - ball table, mommy sock

Basic structures, they can insert elements - some rules of what can be put
where, which pivots come before and which come after

Built around specific words

Minimal/conservative generalization

Problems
‣ Doesn't explain why
‣ Hard to falsify - vague, happens to fit, but can't tell if they are not doing
something more complicated

10

Semantic Relations

Roger Brown

Two word stage

Less conservative generalization
Kids' knowledge is not built around certain words, but is not completely
general either
Based upon semantic relations, narrow categories

‣ Agent + action (Daddy sit)
‣ Agent + object (Mommy sock)

How far do they generalize? Mommy, Daddy, cat are not all the same, even
though they are all agents
Agent vs entity (Dad floor, ball floor)?

11

Artificial Grammar

Gomez and Gerken

Create a completely artificial grammar, expose kids to it, and see what they've
learned

Play a string of sound generated by artificial grammar
1-2 minute exposure to one of two grammars (made of same words)
12-month-olds learn these grammars after very brief exposure

Test children's ability to distinguish previously unheard sequences of sounds
generated by that grammar from those sounds not generated by that
grammar

Head turn preference

Listen longer to new strings generated by the grammar they were just
exposed to than to strings generated by the other grammar

Prefer to listen to new words in their language rather than new words
from a language they've never heard before

What does this tell us about language learning?
Children can learn grammars using statistical probabilites

But...
Real language is complicated
Real language is productive

We learn categories, not all possible word combinations

12

Distributional Model of Grammar Experiment

Gomez and Lakusta

A words paired with X (two-syllable) words, B words paired with Y (onesyllable)
words
All words are made up
One of two languages, the above rules or the reverse
Exposed kids to sequences of sounds that followed the rules

12 month olds
Do kids notice/learn this pattern?
After being trained, they were given unheard strings that followed the rule,
as well as strings that don't follow the rules
In head turn test, the kids listened longer to strings that followed the rules
they had just learned - new combinations with X and Y words that they
never heard during training

Distributional model of grammar - kids know the grammar of a language by
learning that words that occur in similar contexts are similar

This study suggests that kids are doing this - recognizing that there are
rules

13

Will kids learn that there is a correspondence between distributions and
meaning?

Laney & Saffran

Train kids in same language as in the Gomez/Lakusta Experiment

Teach the kids words - each category was one type
Two syllable words were animals, and one syllable words were vehicles

At test, show them two pictures and play a sequence of words
Where does the kid look?

Found that kids would start to look to the picture that was part of the
category that was shown in training
Still an artificial relationship, but different forms of words do relate to
grammatical categories in English

14

Representing Meaning through Collection of Words

Bag of words approach

‣ Scrambled words from various documents

‣ What parts of the meaning of documents can you capture through an
unordered collection of words?

•What the document is about
•Things mentioned in the document

• Documents on similar topics contain similar words

Don't need to know things about natural language, just use word
count

15

Vector Space/Semantic Space/Distributional Model

Table to vector

Each entry is a dimension
The word "film" is a dimension, count is 24, so coordinate of film is
24

The number of dimensions is the number of words that are being counted

Similarity between two documents as proximity in space correlates with similarity

Can be done completely automatically

• Euclidean distance - walking distance from point a to b
• Cosine similarity - angle between them

16

Representing the meaning of words through a collection of context words

Context words are a good indicator of meaning - Similar words tends to occur in similar contexts

Take a context window, i.e. 10 words on either side

• Still just word counting
• Same table to vector approach
• Synonyms and antonyms are close together in vector space

17

Using similarity in vector space
(5 uses)

Search/information retrieval
(Each document is a vector of weighted terms)

Build a thesaurus automatically
(Synonyms & antonyms)

Predict human judgements on how similar pairs of words are

Predict priming effects

Simulate categorization

18

Two issues the come up when we consider whether we represent concepts in our minds using the distributional model

If just distributional, we wouldn't see any similarities between two
seemingly unrelated words (pope, bachelor)

Explaining words through other words - never gets us away from the
symbols - how do you get to the real world?

19

Three word stage - telegraphic speech

Subject, Object, Verb

Understandable in context

Missing linking words that would make the statements clearer
and more conventional

Lacking grammatical morphemes
‣ Functional words (will, on)
‣ Correct forms of verbs

20

Dual-route model

Traditional account of learning the past tense

Regular past tense formation is performed using a rule +ed

Irregular past tense forms are learned exceptions

Children infer the +ed rule and apply it in all cases where they don't have a
memorized irregular word form

Problems
‣ Irregular forms are not completely irregular
Sing/sang, spring/sprang, ring/rang
Stink/stank, drink/drank, sink/sank
‣Novel verbs can be and are inflected using irregular patterns
• Spling/splang, frink/frank or frought if it's cognitive, like think/thought

21

Phonological analogies

Similarity of sounds

Past tense forms of verbs are selected based on the phonological
similarity of the verb to other forms

Learners acquire the very frequent forms

When you know a familiar form, you can decide the forms of new verbs

22

The homophobe problem

‣ There are words that sound identical and yet are inflected in different
ways
• Break/broke
• Brake/braked

‣ A system based entirely on phonological analogy wouldn't allow for this

23

Semantic analogy

Past tense forms of verbs are selected based on the semantic similarity of the verb to other forms