Advanced Course in Psycholinguistics and Neurolinguistics · 2012-07-06 · Psycholinguistics and Neurolinguistics An Example of Artiﬁcial Language Learning Master on Linguistics

INTRO:Is Broca the seat of Syntax?

Language Learning Processes and Strategies

Advanced Course inPsycholinguistics and Neurolinguistics

An Example of Artificial Language Learning

Master on Linguistics(Kepa Erdozia and Itziar Laka)

2011/01/26

Master on Linguistics (Kepa Erdozia and Itziar Laka) Advanced Course in Psycholinguistics and Neurolinguistics



Contents

1 INTRO:

2 Is Broca the seat of Syntax?

3 Language Learning Processes and StrategiesSegmenting Words from a StringLearning GrammarOur Experiments




Contents

1 INTRO:






Contents

1 INTRO:






In previous days...

Propoerties of Language

Biological Basis of LanguageHierarchy of Grammars

Research Methods

Behavioral measuresERPsfMRI

Artificial Grammar Learning

Transitional ProbabilitiesPossible and Impossible GrammarsFSG vs. PSG




In previous days...

Propoerties of LanguageBiological Basis of Language

Hierarchy of GrammarsResearch Methods







In previous days...

Propoerties of LanguageBiological Basis of LanguageHierarchy of Grammars

Research Methods







In previous days...


Research Methods







In previous days...


Research MethodsBehavioral measures

ERPsfMRI






In previous days...


Research MethodsBehavioral measuresERPs

fMRIArtificial Grammar Learning





In previous days...


Research MethodsBehavioral measuresERPsfMRI






In previous days...








In previous days...



Artificial Grammar LearningTransitional Probabilities

Possible and Impossible GrammarsFSG vs. PSG




In previous days...



Artificial Grammar LearningTransitional ProbabilitiesPossible and Impossible Grammars

FSG vs. PSG




In previous days...



Artificial Grammar LearningTransitional ProbabilitiesPossible and Impossible GrammarsFSG vs. PSG




Kaan and Swaab 2002

Is Broca the seat of Syntax?Evidence from Aphasia

Left Anterior Temporal Lobe is also important in syntacticprocessing

Broca’s aphasics do not completely lack knowledge of syntax.

Broca’s aphasics exhibit semantic deficits

Broca’s aphasics not deficit of knowledge but a processing deficit

The brain areas that are damaged in Broca’saphasics need not to be the areas wheresyntactic knowledge is stored.




Kaan and Swaab 2002










Kaan and Swaab 2002










Kaan and Swaab 2002










Kaan and Swaab 2002










Kaan and Swaab 2002










Isolating Syntax

In previous Literature1 Complex vs. Simple sentences

2 Sentences vs. Lists of Words3 Senteces vs. Jabberwocky4 Correct vs. Incorrect sentences




Isolating Syntax

In previous Literature1 Complex vs. Simple sentences2 Sentences vs. Lists of Words

3 Senteces vs. Jabberwocky4 Correct vs. Incorrect sentences




Isolating Syntax

In previous Literature1 Complex vs. Simple sentences2 Sentences vs. Lists of Words3 Senteces vs. Jabberwocky

4 Correct vs. Incorrect sentences




Isolating Syntax

In previous Literature1 Complex vs. Simple sentences2 Sentences vs. Lists of Words3 Senteces vs. Jabberwocky4 Correct vs. Incorrect sentences




Complex vs. Simple Sentences

BROCA (BA 44, 45)Complex conditions involveadditional syntacticoperations

Canonical Word OrderReconstructions vs. WorkingMemory Load




Complex vs. Simple Sentences

BROCA (BA 44, 45)Complex conditions involveadditional syntacticoperationsCanonical Word OrderReconstructions vs. WorkingMemory Load




Sentences vs. Words

no Broca activation

Very simple sentences were used.

Broca is not necessarily involved insyntactic operations

but only comes into play when theprocessing load increases.

Temporal Lobe

sometimes bilateral

patients with morphosyntacticproblems

superior and middle temporal gyri(BA 22, 21)




Jabberwocky and Syntactic Prose

examplesThe mumphy folofel fonged the apole trecon.The infuriated water grabbed the justifieddream.

STSPosterior Superior Temporal SulcusAnterior Superior Temporal Sulcus




Correct vs. Incorrect Sentences

Syntactic violations haveconsequences for the semanticinterpretation.Detecting syntactic errors ofJabberwocky enlarge activity inleft BA45




Kaan and Swaab 2002

Conclusions 11 Is there a specific area for syntax?

NO

2 Temporal LobeAnterior, middle and posterior parts of the Superior andMiddle Temporal Gyri.

3 Are areas unique for syntactic processing?NOBroca and Temporal Lobe’s areas has been activated inprocessing of syntactically unconnected words, lists ofsyllables, semantics, even during music perception




Kaan and Swaab 2002


NO2 Temporal Lobe

Anterior, middle and posterior parts of the Superior andMiddle Temporal Gyri.





Kaan and Swaab 2002


NO2 Temporal Lobe

Anterior, middle and posterior parts of the Superior andMiddle Temporal Gyri.





Kaan and Swaab 2002

Conclusions 2Syntactic processing involves multiple brain areas.

None of these areas are unique for syntax.Brain modularity for language remains unclear.Middle and superior temporal lobes → lexical processing.Anterior temporal lobe → encoding information.Borca → storing non-integrated material.Right areas → Prosody, ambiguity, discourse processing,and error detection.




Kaan and Swaab 2002

Conclusions 2Syntactic processing involves multiple brain areas.None of these areas are unique for syntax.

Brain modularity for language remains unclear.Middle and superior temporal lobes → lexical processing.Anterior temporal lobe → encoding information.Borca → storing non-integrated material.Right areas → Prosody, ambiguity, discourse processing,and error detection.




Kaan and Swaab 2002

Conclusions 2Syntactic processing involves multiple brain areas.None of these areas are unique for syntax.Brain modularity for language remains unclear.

Middle and superior temporal lobes → lexical processing.Anterior temporal lobe → encoding information.Borca → storing non-integrated material.Right areas → Prosody, ambiguity, discourse processing,and error detection.




Kaan and Swaab 2002

Conclusions 2Syntactic processing involves multiple brain areas.None of these areas are unique for syntax.Brain modularity for language remains unclear.Middle and superior temporal lobes → lexical processing.

Anterior temporal lobe → encoding information.Borca → storing non-integrated material.Right areas → Prosody, ambiguity, discourse processing,and error detection.




Kaan and Swaab 2002

Conclusions 2Syntactic processing involves multiple brain areas.None of these areas are unique for syntax.Brain modularity for language remains unclear.Middle and superior temporal lobes → lexical processing.Anterior temporal lobe → encoding information.

Borca → storing non-integrated material.Right areas → Prosody, ambiguity, discourse processing,and error detection.




Kaan and Swaab 2002

Conclusions 2Syntactic processing involves multiple brain areas.None of these areas are unique for syntax.Brain modularity for language remains unclear.Middle and superior temporal lobes → lexical processing.Anterior temporal lobe → encoding information.Borca → storing non-integrated material.

Right areas → Prosody, ambiguity, discourse processing,and error detection.




Kaan and Swaab 2002

Conclusions 2Syntactic processing involves multiple brain areas.None of these areas are unique for syntax.Brain modularity for language remains unclear.Middle and superior temporal lobes → lexical processing.Anterior temporal lobe → encoding information.Borca → storing non-integrated material.Right areas → Prosody, ambiguity, discourse processing,and error detection.




Segmenting Words from a StringLearning GrammarOur Experiments

Language learning processes and strategies

Grammar Hierarchy

Finite Structure Grammars: [AB][AB][AB][AB][AB][AB]

Phrase Structure Grammars: [A[A[A[A[A[AB]B]B]B]B]B]

Transformational Grammars

Hierarchical Organization of Grammar

The man saw the woman with binoculars

Increasing Hierarchical Structure

sounds ⇒ words ⇒ phrases ⇒ sentences






Grammar Hierarchy













Grammar Hierarchy













Grammar Hierarchy













Grammar Hierarchy













Grammar Hierarchy













Grammar Hierarchy













Grammar Hierarchy







sounds

⇒ words ⇒ phrases ⇒ sentences






Grammar Hierarchy







sounds ⇒ words

⇒ phrases ⇒ sentences






Grammar Hierarchy







sounds ⇒ words ⇒ phrases

⇒ sentences






Grammar Hierarchy







sounds ⇒ words ⇒ phrases ⇒ sentencesMaster on Linguistics (Kepa Erdozia and Itziar Laka) Advanced Course in Psycholinguistics and Neurolinguistics




Segmenting words from a string

Saffran et al. 1996 → Transitional Probability: 8m.o.babies 2min of training.Pena et al. 2002 → Learning dependencies only withsubliminal pauses (50 ms.).McNealy et al. 2006 → fMRI replication of Saffran et al.1996.





Learning grammar

Morgan & Newport 1981 → Reference-world facilitatessyntax learning.Morgan, Meier, and Newport 1987 → Prosody, FunctionWords, and Morphological Concord facilates syntaxlearning.Saffran 2001 → Transitional Probabilities learninggrammars (Predictive dependencies).Thompson & Newport 2007 → Transformations (optionalelements, movement...) Statitiscal Computation learningsyntax.Musso et al. 2003 → UG vs. NON-UGFriederici et al. 2006 → [AB][AB] vs. [A[AB]B]






AIM

To see the progressive learning of an artificial language which characteristicskeep the core syntactic properties of natural languages like the recursivity,categories, argument structure and phrase structure architecture, excludingany semantics and prosody in order to avoid any cue but distributional cue.

Hypothesis

There is a progression in the learning from sounds to words, from words tophrases, and from phrases to sentences.

Question

Is it possible to learn a complex linguistic structure (PSG) by means ofdistributional cues only?

Answer 1: No (Morgan et al. 1987)

Answer 2: Yes (Saffran 2001; Thompson & Newport 2007)






AIM


Hypothesis


Question









AIM


Hypothesis


Question








Pilot Study 1

Our Artifical LanguageThe Vocabulary

DET: re, Zo, Sa, Su, ri

REL: na, ve, zo, zi, nu

Noun: debi, gapi, pogue, tafe, kelo, laku, fisa, motu, suma

Vb1: besi, dibo, goda, puki, tefo

Vb2: tike, lume, fagu, mipa, sole

The Grammar

S → DP + VPDP → NP + DNP → (RelC) + NRelC → VP + RelVP → (DP) + V





Pilot Study 1

Our Artifical LanguageThe Vocabulary

DET: re, Zo, Sa, Su, ri

REL: na, ve, zo, zi, nu

Noun: debi, gapi, pogue, tafe, kelo, laku, fisa, motu, suma

Vb1: besi, dibo, goda, puki, tefo

Vb2: tike, lume, fagu, mipa, sole

The Grammar






Pilot Study 1

The Sentences of the Language1. [N + D] + V12. [ [ [V1 +R] + N]] + D]]] + V13. [[[[[N + D] + V2 ] R] + N] + D] + V14. [[[[[[[V1 +R] + N] + D] + V2 ] R] + N] + D] + V15. [N + D] + [ [N + D] + V2]6. [[[V1 +R] + N] + D] + [ [N + D] + V2]7. [[[[[N + D] + V2 ] R] + N] + D] + [[N + D] + V2]8. [N + D] + [[[[V1 + R] + N] + D] + V2]9. [N + D] + [[[[[[N + D] + V2 ] R] + N] + D] + V2]

10. [[[V1 + R] + N] + D] + [[[[V1 + R] + N] + D] + V2]





Pilot Study 1: FSG vs. PSGTHE SENTENCES GENERATED BY THE PSG

The Sentences of the Language

1. [N + D] + V1

2. [ [ [V1 +R] + N]] + D]]] + V1

3. [[[[[N + D] + V2 ] R] + N] + D] + V1

4. [[[[[[[V1 +R] + N] + D] + V2 ] R] + N] + D] + V1

5. [N + D] + [ [N + D] + V2]

6. [[[V1 +R] + N] + D] + [ [N + D] + V2]

7. [[[[[N + D] + V2 ] R] + N] + D] + [[N + D] + V2]

8. [N + D] + [[[[V1 + R] + N] + D] + V2]

9. [N + D] + [[[[[[N + D] + V2 ] R] + N] + D] + V2]

10. [[[V1 + R] + N] + D] + [[[[V1 + R] + N] + D] + V2]

THIS FSG CAN GENERATE ALL THESE SENTENCES

”the fundamental aim in the linguistic analysis of a language L is toseparate the grammatical sequences which are the sentences of Lfrom the ungrammatical sequences and to study the structure of thegrammatical sequences. The grammar of L will thus be a device thatgenerates all of the grammatical sequences of L and none of theungrammatical one‘’ (Chomsky 1957 [2nd ed., 2002: 13]).







1. [N + D] + V1

2. [ [ [V1 +R] + N]] + D]]] + V1

3. [[[[[N + D] + V2 ] R] + N] + D] + V1

4. [[[[[[[V1 +R] + N] + D] + V2 ] R] + N] + D] + V1

5. [N + D] + [ [N + D] + V2]

6. [[[V1 +R] + N] + D] + [ [N + D] + V2]

7. [[[[[N + D] + V2 ] R] + N] + D] + [[N + D] + V2]

8. [N + D] + [[[[V1 + R] + N] + D] + V2]

9. [N + D] + [[[[[[N + D] + V2 ] R] + N] + D] + V2]

10. [[[V1 + R] + N] + D] + [[[[V1 + R] + N] + D] + V2]


”the fundamental aim in the linguistic analysis of a language L is toseparate the grammatical sequences which are the sentences of Lfrom the ungrammatical sequences and to study the structure of thegrammatical sequences. The grammar of L will thus be a device thatgenerates all of the grammatical sequences of L and none of theungrammatical one‘’ (Chomsky 1957 [2nd ed., 2002: 13]).







1. [N + D] + V1

2. [ [ [V1 +R] + N]] + D]]] + V1

3. [[[[[N + D] + V2 ] R] + N] + D] + V1

4. [[[[[[[V1 +R] + N] + D] + V2 ] R] + N] + D] + V1

5. [N + D] + [ [N + D] + V2]

6. [[[V1 +R] + N] + D] + [ [N + D] + V2]

7. [[[[[N + D] + V2 ] R] + N] + D] + [[N + D] + V2]

8. [N + D] + [[[[V1 + R] + N] + D] + V2]

9. [N + D] + [[[[[[N + D] + V2 ] R] + N] + D] + V2]

10. [[[V1 + R] + N] + D] + [[[[V1 + R] + N] + D] + V2]


THEN WE GENERATED TWO NEW CONDITIONS

Material generated by the PSG

11. [[[[[[[[[N+D]+V2]+R]+N]+D]+V2]+R]+N]+D]+V1

Material not allowed by the PSG

X NDNDV2RNDNDV2





Pilot Study 1: Design

Series of 10 training (12 min) and testing (5 min). Total = 2h45

Training

1. [N + D] + V1

2. [ [ [V1 +R] + N]] + D]]] + V1

3. [[[[[N + D] + V2 ] R] + N] + D] + V1

4. [[[[[[[V1 +R] + N] + D] + V2 ] R] + N] + D] + V1

5. [N + D] + [ [N + D] + V2]

6. [[[V1 +R] + N] + D] + [ [N + D] + V2]

7. [[[[[N + D] + V2 ] R] + N] + D] + [[N + D] + V2]

8. [N + D] + [[[[V1 + R] + N] + D] + V2]

9. [N + D] + [[[[[[N + D] + V2 ] R] + N] + D] + V2]

10. [[[V1 + R] + N] + D] + [[[[V1 + R] + N] + D] + V2]

Testing

1 Non-Syllables → Rejected by the participants

2 Non-Words → TP > 0, Sounds

3 Words → Combining syllables into words

4 Phrases → Combining words into phrases

5 Sentences → Highest level of complexity

6 Deviant Phrases → Ungrammatical phrases

7 Deviant Sentences → Ungrammatical sentences

Task: Scalar grammaticality judgment (from 0 to 5)







Training

1. [N + D] + V1

2. [ [ [V1 +R] + N]] + D]]] + V1

3. [[[[[N + D] + V2 ] R] + N] + D] + V1

4. [[[[[[[V1 +R] + N] + D] + V2 ] R] + N] + D] + V1

5. [N + D] + [ [N + D] + V2]

6. [[[V1 +R] + N] + D] + [ [N + D] + V2]

7. [[[[[N + D] + V2 ] R] + N] + D] + [[N + D] + V2]

8. [N + D] + [[[[V1 + R] + N] + D] + V2]

9. [N + D] + [[[[[[N + D] + V2 ] R] + N] + D] + V2]

10. [[[V1 + R] + N] + D] + [[[[V1 + R] + N] + D] + V2]

Testing















Training

1. [N + D] + V1

2. [ [ [V1 +R] + N]] + D]]] + V1

3. [[[[[N + D] + V2 ] R] + N] + D] + V1

4. [[[[[[[V1 +R] + N] + D] + V2 ] R] + N] + D] + V1

5. [N + D] + [ [N + D] + V2]

6. [[[V1 +R] + N] + D] + [ [N + D] + V2]

7. [[[[[N + D] + V2 ] R] + N] + D] + [[N + D] + V2]

8. [N + D] + [[[[V1 + R] + N] + D] + V2]

9. [N + D] + [[[[[[N + D] + V2 ] R] + N] + D] + V2]

10. [[[V1 + R] + N] + D] + [[[[V1 + R] + N] + D] + V2]

Testing















Training

1. [N + D] + V1

2. [ [ [V1 +R] + N]] + D]]] + V1

3. [[[[[N + D] + V2 ] R] + N] + D] + V1

4. [[[[[[[V1 +R] + N] + D] + V2 ] R] + N] + D] + V1

5. [N + D] + [ [N + D] + V2]

6. [[[V1 +R] + N] + D] + [ [N + D] + V2]

7. [[[[[N + D] + V2 ] R] + N] + D] + [[N + D] + V2]

8. [N + D] + [[[[V1 + R] + N] + D] + V2]

9. [N + D] + [[[[[[N + D] + V2 ] R] + N] + D] + V2]

10. [[[V1 + R] + N] + D] + [[[[V1 + R] + N] + D] + V2]

Testing













Pilot Study 1: Results Across Conditions (n = 6)

Word SegmentationPreference to the structured conditionsImpossible to distinguish correct and incorrect structures





Pilot Study 1: Results Across Sessions (n = 6)

Word learned from the beginning AND The performance was decreasing

Conclusions

The experiment was too long, participants got tired

Words easily recognized

Some kind of preference to structure





Pilot Study 1: Results Across Sessions (n = 6)

Word learned from the beginning AND The performance was decreasing

Conclusions

The experiment was too long, participants got tired

Words easily recognized

Some kind of preference to structure





Pilot Study 2

Aim

Progressive learning, core syntactic properties, no semantics, no prosody

Design

Extend the experiment in 5 days

Syllable Detection Task in the training in order to increase the attentionof the participants.

Level driven Task: Testing single units of complexity (words, phrases, ...)

Transitional Probabilities = 0 phrases and sentences in the testing

Increase the amounto of words of the Vocabulary

Phrase Structure Grammar vs. Finite State Grammar





Pilot Study 2

Aim


Design











Pilot Study 2

Aim


Design











Pilot Study 2

Aim


Design











Pilot Study 2

Aim


Design











Pilot Study 2

Aim


Design











Pilot Study 2

Aim


Design











Pilot Study 2: The Language

The Vocabulary

DET like elements: ga, gi, to, fu, mi

COMP like elements: li, no, di, do, lu

NOUN like elements: pare, tero, kodi, buna, dugo, faru, cena, sige,gimu, monu, nulli, llajo, lebi, gofe, pulle, case

VERB1 like elements: petu, tine, quira, zori, dallo, geni, soni, fisu

VERB2 like elements: tade, juma, mellu, noe, kuza, poque, bepi, jafo

The Grammar


BUT






The Vocabulary






The Grammar


BUT






The Vocabulary






The Grammar


BUT





Pilot Study 2

Procedure (extended in 5 days)Day 1: Training + TestingDay 2: Double trainingDay 3: Training + TestingDay 4: Double trainingDay 5: Training + Testing (TP=0)





Pilot Study 2: Training10 sentences types range from 5 to 14 syllables (200 sentences = 24 min)

1. [N + D] + V12. [ [ [V1 +R] + N]] + D]]] + V13. [[[[[N + D] + V2 ] R] + N] + D] + V14. [[[[[[[V1 +R] + N] + D] + V2 ] R] + N] + D] + V15. [N + D] + [ [N + D] + V2]6. [[[V1 +R] + N] + D] + [ [N + D] + V2]7. [[[[[N + D] + V2 ] R] + N] + D] + [[N + D] + V2]8. [N + D] + [[[[V1 + R] + N] + D] + V2]9. [N + D] + [[[[[[N + D] + V2 ] R] + N] + D] + V2]

10. [[[V1 + Rel] + N] + D] + [[[[V1 + R] + N] + D] + V2]Days 2 and 4 Double Training (400 sentences = 48 min)

Task

High Frequency Syllable identification alternating last and first syllables ofbisyllabic words.







10. [[[V1 + Rel] + N] + D] + [[[[V1 + R] + N] + D] + V2]

Days 2 and 4 Double Training (400 sentences = 48 min)

Task









Task









Task






Pilot Study 2: TESTING

Task: Scalar gammaticality decision

Words (84 items)

The words of the vocabulary → Monosyllabic and bisyllabic non-words

Phrases (80 items)

DP: ND DNCP: V1C CV1VP: NDV2 V2DNNP: V1CN NCV1

Sentences (80 items)

NDV1 NCV1NDNDV2C NDV2DV1NDV2CNDV1 NCNDV2DV1NDV1CNDV2 NDV1DCNV2







Words (84 items)


Phrases (80 items)










Words (84 items)


Phrases (80 items)










Words (84 items)


Phrases (80 items)










TP = 0 Phrases (32 items)


TP = 0 Sentences (32 items)


Grammars (days 1 and 3 20 items; day 5 40 items)

PSG NDV2CNDV2CNDV1 FSG NDNDV2NDNDV2












PSG NDV2CNDV2CNDV1 FSG NDNDV2NDNDV2





Pilot Study 2: Results (n = 4)





Pilot Study 2: Results WORDS (n = 4)















Pilot Study 2: Results PHRASES (n = 4)




















Pilot Study 2: Results SENTENCES (n = 4)















Pilot Study 2: Results GRAMMARS (n = 4)





Pilot Study 2: Results TP = 0 (n = 4)





Pilot Study 2: Results TP = 0 (n = 4)





Pilot Study 2: Discussion

Word Recognition

The words increase the scores across days; non-words remainSo, the vocabulary was not completely learned

Monosyllabic and Bisyllabic asymmetry

Phrase and Sentence Recognition

The scores of grammatical and ungrammatical phrases icrease.So, the structure of the language was not learned.

TP = 0 Material

Structured strings and non-structured strings both similar scores.

Grammar Preference

Small preference for the PSG only the first day.






Word Recognition





TP = 0 Material


Grammar Preference







Word Recognition





TP = 0 Material


Grammar Preference







Word Recognition





TP = 0 Material


Grammar Preference






Pilot Study 3

Prosodic Component

After two vain attempts trying to teach participants the grammar of ourartificial language, we decided to introduce prosodic cues to see if it wouldhelp the participants.

The artificial language of the third experiment had three linguisticcomponents: the Lexical component, the Grammatical component, and theProsodic component. The Semantic component of language remained out ofour third artificial language.

Design

5 days experiment

During the training: Syllable Detection Task








Pilot Study 3

Prosodic Component

After two vain attempts trying to teach participants the grammar of ourartificial language, we decided to introduce prosodic cues to see if it wouldhelp the participants.The artificial language of the third experiment had three linguisticcomponents: the Lexical component, the Grammatical component, and theProsodic component. The Semantic component of language remained out ofour third artificial language.

Design

5 days experiment









Pilot Study 3

Prosodic Component


Design

5 days experiment









Pilot Study 3

Prosodic Component


Design

5 days experiment









Pilot Study 3

Prosodic Component


Design

5 days experiment









Pilot Study 3

Prosodic Component


Design

5 days experiment









Pilot Study 3

Prosodic Component


Design

5 days experiment










The Vocabulary

16 bisyllabic words like Nouns: budo, debi, gapi, poge, tafe, kelo, laku,fisa, motu, suma, cheno, zuvi, vomu, seko, chito, peja

5 monosyllabic words like Determiners: re, jo, cha, chu, ri

16 bisyllabic words like Verbs8 behaving like intransitives: besi, dibo, goda, puki, tefo, jugi, rova, rani8 behaving like transitives: tike, lume, fagu, mipa, sole, kaje, duza, fune

5 monosyllabic words like Complementaizers: na, ve, zo, zi, nu

The Grammar


BUT






The Vocabulary





The Grammar


BUT






The Vocabulary





The Grammar


BUT





Pilot Study 3: Prosody

Every sentences type of the experimental material had aestablished pitch pattern. The pitch pattern was obtained fromthe pitch pattern of the same structures in a natural Head Finallanguage. We applied that picht pattern directly to thesentences of our artificial language.Concerning to the duration of the phonemes, we appliedproportionally the absolute values recorded from Basque to thesentences of the experiment. That is, the duration of aphoneme in a given experimental sentence was proportional tothe duration of the phoneme itself and the duration of thephoneme in the same structural position of Basque.





Pilot Study 3

ProcedureDay 1: Training + TestingDay 2: Double trainingDay 3: Training + TestingDay 4: Double trainingDay 5: Training + Testing (TP=0)






1 [N D] Vintr

2 [[Vintr C] N D] Vintr

3 [[N D Vtr C] N D] Vintr

4 [[[[Vintr C] N D] Vtr C] N D] Vintr

5 [N D] N D Vtr

6 [[Vintr C] N D] N D Vtr

7 [[N D Vtr C] N D] N D Vtr

8 [N D] [[Vintr C] N D] Vtr

9 [N D] [[N D Vtr C] N D] Vtr

10 [[Vintr C] N D] [[Vintr C] N D] Vtr


Task: High Frequency Syllable identification.






1 [N D] Vintr




5 [N D] N D Vtr













1 [N D] Vintr




5 [N D] N D Vtr














Words (84 items)


Phrases (80 items)

Testing Phrasescorrect phrases deviant phrases

[ND] *[DN][Vintr C] *[CVintr ][NDVtr ] *[NCVtr ][Vintr CN] *[Vintr DN]


Testing Sentencescorrect sentences deviant sentences

[N D] Vintr *N C Vintr

[N D] N D Vtr *N D Vtr D Vintr

[[N D Vtr C] N D] Vintr *N C N D Vtr D Vintr

[N D [Vintr C N D] Vtr *[N D [Vintr D C N Vtr







Words (84 items)


Phrases (80 items)















Words (84 items)


Phrases (80 items)















Words (84 items)


Phrases (80 items)















New Correct Phrases[N D] [Vintr C] [NDVtr ] [Vintr CN]

budo re besi na motu chu tike besi ve budodebi jo dibo ve suma ri lume dibo zo gapi

gapi cha goda zo jeno re fagu goda zi debipoge chu puki zi zuvi jo mipa puki nu tafe

tafe ri tefo nu vomu cha sole tefo na poguekelo re jugui na seko chu kaje jugui ve kelolaku jo rova ve chito ri duza rova zo lakufisa cha rani zo peja re fune rani zi fisa

Structures of the New Incorrect Phrases[CN] [CV] [NVD] [CVN]







New Correct Sentences[N D] Vintr [N D] N D Vtr [[N D Vtr C] N D] Vintr [N D [Vintr C N D] Vtr

budo re besi budo jo peja ri tike motu chu tike na peja jo rani gapi jo besi ve budo re tike

debi jo goda debi cha chito jo lume suma ri lume ve chito chu rova debi re dibo zo gapi jo fune

gapi cha dibo gapi chu seko re mipa cheno re fagu zo seko cha jugui tafe chu goda zi debi cha duza

poge chu tefo pogue ri vomu chu sole zuvi jo mipa zi vomu ri tefo kelo cha puki nu tafe chu mipa

tafe ri puki tafe re zuvi cha kaje vomu cha sole nu zuvi re puki fisa re tefo na pogue ri kaje

kelo re jugui kelo jo suma re duza seko chu kaje na suma jo dibo laku ri jugui ve kelo re lume

laku jo rova laku cha cheno ri fune chito ri duza ve cheno cha goda pogue cha rova zo laku jo sole

fisa cha rani fisa chu motu jo fagu peja re fune zo motu ri besi budo chu rani zi fisa cha fagu

Structures of the New Incorrect Sentences[NCV] [NVDCV] [NVVNCV] [NCDCVDRV]







Testing GrammarsPhrase Structure Grammar Finite State Grammar

NDVtr CNDVtr CNDVintr NDNDVtr CNDNDVtr





Pilot Study 3: RESULTS (n = 9) WORDS

Significant interaction between Day and Correctness.Including length factor, interaction of Lenght and Correcteness(F (1, 5) = 4.3; p < .01).





Pilot Study 3: RESULTS (n = 9) PHRASES

Effect of Condition (F (1, 6) = 20.7; p < .01).





Pilot Study 3: RESULTS (n = 9) SENTENCES

Significant interaction (F (2, 12) = 18.3; p < .001) between Day andCorrecteness.Shorts easier than Long





Pilot Study 3: RESULTS (n = 9) GRAMMARS

No signficant interaction.(Condition: F (1, 6) = 3.18; p = .12 and Day: F (2, 12) = 2.1; p = .17)





Pilot Study 3: RESULTS (n = 9) TP = 0

Trend for new-phrases in comparison with new-pseudophrases(F (1, 6) = 5.6; p = .055)





General Discussion

Word Learning

Large vocabulary learning without semantics nor prosody

Monosyllabic vs. Bisyllabic asymmetry

Syntactic Pattern Learning

Only with prosody

New Material

Ratings close to illegal structures

However, higher scores to new combinations respecting Grammar

Grammar Generalization

No evidence for PSG rather than FSG in longer structures.





General Discussion

Word Learning




Only with prosody

New Material









General Discussion

Word Learning




Only with prosody

New Material









General Discussion

Word Learning




Only with prosody

New Material









The End


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