2 |
On the Utility of Conjoint and Compositional Frames and Utterance
|
|
|
|
BASE
|
|
Show details
|
|
3 |
Simulating the referential properties of Dutch, German and English Root Infinitives in MOSAIC
|
|
|
|
BASE
|
|
Show details
|
|
4 |
Does chess need intelligence? – A study with young chess players
|
|
|
|
BASE
|
|
Show details
|
|
7 |
Modelling the developmental patterning of finiteness marking in English, Dutch, German and Spanish using MOSAIC
|
|
|
|
BASE
|
|
Show details
|
|
8 |
Understanding the Developmental Dynamics of Subject Omission: The Role of Processing Limitations in Learning
|
|
|
|
BASE
|
|
Show details
|
|
9 |
Simulating the Noun-Verb Asymmetry in the Productivity of Children’s Speech
|
|
|
|
BASE
|
|
Show details
|
|
10 |
Linking working memory and long-term memory: A computational model of the learning of new words
|
|
Jones, G; Gobet, F; Pine, J M. - : Blackwell Publishing. The definitive version is available at onlinelibrary.wiley.com, 2007
|
|
BASE
|
|
Show details
|
|
11 |
Modelling the Development of Children’s use of Optional Infinitives in Dutch and English using MOSAIC
|
|
|
|
BASE
|
|
Show details
|
|
12 |
Unifying cross-linguistic and within-language patterns of finiteness marking in MOSAIC
|
|
|
|
BASE
|
|
Show details
|
|
13 |
On the resolution of ambiguities in the extraction of syntactic categories through chunking
|
|
|
|
BASE
|
|
Show details
|
|
14 |
Simulating the cross-linguistic development of optional infinitive errors in MOSAIC.
|
|
|
|
BASE
|
|
Show details
|
|
15 |
Simulating optional infinitive errors in child speech through the omission of sentence-internal elements.
|
|
|
|
BASE
|
|
Show details
|
|
16 |
Resolving ambiguities in the extraction of syntactic categories through chunking.
|
|
|
|
BASE
|
|
Show details
|
|
17 |
Simulating the temporal reference of Dutch and English Root Infinitives.
|
|
|
|
BASE
|
|
Show details
|
|
18 |
Modelling syntactic development in a cross-linguistic context
|
|
|
|
BASE
|
|
Show details
|
|
19 |
The role of input size and generativity in simulating language acquisition.
|
|
|
|
Abstract:
This paper presents an analysis of the role of input size and generativity (ability to produce novel utterances) in simulating developmental data on a phenomenon in first language acquisition. An existing model that has already simulated the basic phenomenon is trained on input sets of varying sizes (13,000 to 40,000 utterances). The ability of the model to produce novel utterances is also manipulated. Both input size and generativity affect the fits for later stages of development. Higher generativity improves fits for later stages, but worsens them for early stages, suggesting generativity is best increased as a function of mean length of utterance (MLU). The effect of training set is variable. Results are discussed in terms of optimal training sets for simulations, and children’s developing ability to produce utterances beyond the input they have heard.
|
|
Keyword:
acquisition of language; computational modelling; generativity; input; MLU; MOSAIC; optional infinitive; Wexler
|
|
URL: http://bura.brunel.ac.uk/handle/2438/781
|
|
BASE
|
|
Hide details
|
|
20 |
Modelling children's negation errors using probabilistic learning in MOSAIC.
|
|
|
|
BASE
|
|
Show details
|
|
|
|