Design of artificial languages to study language perception and its evolutionary origins

Matthew G. Collison

Initial aimsMy initial aims for the study were:• Develop an artificial language that behaviourally tests

specific components of language perception. • Design an artificial language that integrates these

components of language to indicate processing of perception.

• Design an artificial language that spans the linguistic perception capability across the species to determine the evolutionary conservation of language perception.

• Optimise the paradigm for future imaging studies.

Backgroun Literature • Phonetic identification • Petkov ’09

• Statistical segmentation• Saffran ’96• Abla ’08

• Structural perception • Federici ‘06

• Comparative structural perception studies in humans and monkeys

• Fitch and Hauser ’05• Saffran and Hauser ‘08

Aims of the artificial languageI designed an artificial language to integrate the three

theories into a comparable function and develop an overall model of language perception summarising interaction between the 3 components.

• I included a tonal and word based parameter which gave an indication as to influence of statistical and phonetic input into different levels of structure.

• I included a multiple exemplar function to give two levels of structural complexity.

• I included manipulated the discriminatory testing to allow us to behaviourally evaluate to what extent subject rely on statistics or rule breaks to discriminate structure at different levels.

The Languages Basic structure from Saffran and HauserSequence A phrase + B phrase + (C phrase)A phrase A + (D)B phrase C + FC phrase C + (G)( ) letters in brackets are optional elements

Rules present in this language:1. The basic structure must include A –C – F – 2. If D is present it must follow A.3. If G is present it must follow C

Subclass associations used in word languages

Subclass words used

A Biff hep

C Cav lum

D Klor pell

F Dupp loke

G Jux pilk

Subclass associations used in tone languages

Subclass tones used

A A# G

C E A

D D F

F C G#

G F# B

10 possible Sequences from grammatical structure

ADCGFCACGFCGADCFCGADCFCACFCGACGFCADCGFACFCADCFACGF

Procedural Paradigm

TrainingExposure sequences

Testing Grammatical

ADCGFC ADCFCGACGFCG ACGFC

ADCFC ADCGFACFCG ACGF

ACFC Ungrammatical

ADCF ADGCFCADFCGAGFCD

AFCD

There are two stages to the experimental procedure 1. Training – For 5 minutes participants

are exposed to training programme2. Testing participant are presented

with completely novel stimuli and have to determine whether they think it is grammatical or ungrammatical.

Results

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Experiment 1 – word based local structure

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Experiment 2 - tone based local structure

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Figure 2. A graph to show performance in discriminating local structure in tone based languages after 5 minutes exposure to the structure.

Figure 1. A graph to show performance in discriminating local structure in non sense word based languages after 5 minutes exposure to the structure.

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Experiment 3 – word based global structure

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tone predictive PSG0%5%

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Experiment 4 - tone based global structure

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Figure 3. A graph to show performance in discriminating global structure in non sense word based languages after 8 minutes exposure to the structure.

Figure 4. A graph to show performance in discriminating global structure in tone based languages after 8 minutes exposure to the structure.

Further analysis of local structure

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Further analysis of global structure

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Relationship between performance and number of low transi-tional probabilities

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Words PSG Tones PSG0%

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Relationship between performance and number of rule violations

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Conclusions

• We have designed an artificial language that has advantages for human and monkey study:

• 1. Behaviour can be evaluated without giving feedback (monkeys will not be given feedback).

• 2. Tone languages can be created. Nonsense words (speech) can be used if needed.

• 3. We can evaluate if subjects (human or monkey) rely on statistics or rule breaks.

• Our human data suggests that subjects can learn local and global structure in both word based and tonal artificial languages.

Next Steps:

• We believe the paradigm which has now been behaviorally tested in humans is:

• Ready for monkey behavior (using preferential looking paradigms)• Ready for fMRI study.

• Long term objective: Through comparative behavior and fMRI, the paradigm that we have developed has the potential to reveal what would have been the precursory network in the nonhuman primate brain that evolved to support language in humans.

Thank you for your attention.