國立虎尾科技大學 |

A Computational Model of the Acquisition of Mental State Verbs.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	A Computational Model of the Acquisition of Mental State Verbs./
作者:	Barak, Libby.
面頁冊數:	1 online resource (159 pages)
附註:	Source: Dissertation Abstracts International, Volume: 78-08(E), Section: B.
Contained By:	Dissertation Abstracts International78-08B(E).
標題:	Computer science. -
電子資源:	click for full text (PQDT)
ISBN:	9781369667332

A Computational Model of the Acquisition of Mental State Verbs.
Barak, Libby.

A Computational Model of the Acquisition of Mental State Verbs. - 1 online resource (159 pages)

Source: Dissertation Abstracts International, Volume: 78-08(E), Section: B.

Thesis (Ph.D.)--University of Toronto (Canada), 2016.

Includes bibliographical references

Children first use verbs to refer to inner mental states, such as thoughts and beliefs, only towards their 4th birthday. Presenting this ability serves as important evidence of the stage of cognitive development of a child since it entails an ability to conceptualize mental states. This developmental milestone is necessary for children to engage in social interaction since appropriate interaction relies on directing the interaction and anticipate actions surrounding them given the mental states of others. Thus far, psycholinguistic models have been widely focused on the development of cognitive and linguistic skills required to enable the expression of mental states by children. However, while computational models have proved to be a useful tool in studying the developmental trajectory of similar language acquisition phenomena, no computational model to our knowledge has been used to analyze the linguistic development required for the expression of mental states. In this thesis, I present a computational model used to analyze the way linguistic development plays a role in learning to express mental state verbs.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369667332Subjects--Topical Terms:

573171
Computer science.
Index Terms--Genre/Form:

554714
Electronic books.

A Computational Model of the Acquisition of Mental State Verbs.
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500 $a Source: Dissertation Abstracts International, Volume: 78-08(E), Section: B.
500 $a Adviser: Suzanne Stevenson.
502 $a Thesis (Ph.D.)--University of Toronto (Canada), 2016.
504 $a Includes bibliographical references
520 $a Children first use verbs to refer to inner mental states, such as thoughts and beliefs, only towards their 4th birthday. Presenting this ability serves as important evidence of the stage of cognitive development of a child since it entails an ability to conceptualize mental states. This developmental milestone is necessary for children to engage in social interaction since appropriate interaction relies on directing the interaction and anticipate actions surrounding them given the mental states of others. Thus far, psycholinguistic models have been widely focused on the development of cognitive and linguistic skills required to enable the expression of mental states by children. However, while computational models have proved to be a useful tool in studying the developmental trajectory of similar language acquisition phenomena, no computational model to our knowledge has been used to analyze the linguistic development required for the expression of mental states. In this thesis, I present a computational model used to analyze the way linguistic development plays a role in learning to express mental state verbs.
520 $a The computational model in this thesis offers an integrated framework that simultaneously models several of the cognitive and linguistic factors in the acquisition of mental state verbs. The cognitive factor simulates the difficulty in attending to mental states, while the linguistic properties represent the typical semantic and syntactic properties of use of mental state verbs, e.g., reference to mental states using a sentential complement syntactic structure. The experimental work in this thesis replicates psycholinguistic observations from the child acquisition of mental state verbs. The results of these experiments shed light on the facilitating role of certain linguistic properties of mental state verbs in learning to verbally refer to mental meanings. Importantly, I achieve these results within the context of naturalistic language input that mimics the complexity and diversity of use of mental state verbs and verbs from additional semantic classes in child-directed speech. Finally, I present a novel extension to an existing computational model of verb argument structure learning that enables the simultaneous and incremental learning of verb classes. The novel model offers a probabilistic framework to analyze monotonically growing verb classes in comparison to previously offered batch models that limit the capabilities of the computational simulation. Moreover, this model gives support to the importance of an additional linguistic property of mental state verb, i.e., the role of their use with syntactic structures other than the well-studied co-occurrence with sentential complement syntax in child-directed speech. Finally, I show the contribution of this novel computational component in comparison with previous computational models in a wider context of argument structure learning.
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