central issues
DESCRIPTION
Central issues. For both experimental and modeling field it is important to start from theory A common theory (and a common lexicon ) will help building the interface between modelers and experimentalist Features mean different things for different people! - PowerPoint PPT PresentationTRANSCRIPT
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Central issues
• For both experimental and modeling field it is important to start from theory
• A common theory (and a common lexicon) will help building the interface between modelers and experimentalist– Features mean different things for different people! – Make your research question as precise as possible
• Important step taken in this workshop!
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Central issues
• Experimentalists– Need more data, more experiments (to test theories)
• Modelers– Need better models which can predict future data
• Ideally, models make predictions, which can be tested experimentally, leading to improved models…
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Central issues
• Theory of language acquisition– Bottom-up: often aimed for in speech research
• Hard to determine relevant features, categories, etc.• Often unsuccessful: lacking insight into which data/features are
important for the language learner
– Top-down: example Petra Hendriks and colleagues• Many assumption regarding relevant features, categories, etc.
– Or both?– Integration of information from various domains
(Feldman)
• Is ‘good enough’ sufficient?4
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Central issues
• Input– Too rich/not rich enough?– How much input is needed?– How are the relevant cues in the input selected
by the learner?– What filters/constraints does the language
learner use?
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Bold claims about early language acquisition
Kuhl et al. (2008)
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Recurrent issues
• Experiments– Only trust experimental results that are
replicable!• As a community we are responsible for replicating
studies and informing the field about non-replicable results
• More communication within the field
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Recurrent issues
• Models need to be built on reliable experimental results/claims– Communication between modelers and
experimentalists is essential
• Models need to make sure that experimentalists know what good models are– Communication between modelers and
experimentalists is essential
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Central issues
• Development– How can it be described?– What triggers development?– Longitudinal (perception) studies are rare
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Recurrent issues
• Experiments– Do the dependent measures (often looking time)
reflect underlying knowledge and processes sufficiently?
• Are time course measures more insightful?• Discrimination is not categorization!
– Selection of stimulus materials is crucial• Sufficiently informed by linguistic theory?• Comparison of stimuli materials in similar paradigms to
gain insight into which cues in the materials help/hinder learning
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Recurrent issues
• Models need to be cognitively plausible• Different types of models:
– Models are not just fancy calculators (although they can be), – but preferably also make predictions and provide insight into
mechanisms of acquisition
• Models give insight into development– Of individual children?– Or language learners in general?
• Urgent need to compare models!• Do modelers of acquisition of syntax encounter the same
issues as those modeling early speech perception?11
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Other issues
• Cross-linguistic studies (non-Indoeuropean)• Variation
– In input– Between learners (individual differences)
• Learning in the lab vs. learning in real life– Feedback– Role of social interaction
• Abstraction/Generalization• Relation perception/production?
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Share data and
For language resources and technology infrastructure !
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Which conferences could be meeting places?
…
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15Thanks to all participants! Let’s meet again soon!