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Probabilistic Evaluation of Comparat...
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Munteanu, Andrei.
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Probabilistic Evaluation of Comparative Reconstructions.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Probabilistic Evaluation of Comparative Reconstructions./
作者:
Munteanu, Andrei.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2024,
面頁冊數:
246 p.
附註:
Source: Dissertations Abstracts International, Volume: 85-10, Section: A.
Contained By:
Dissertations Abstracts International85-10A.
標題:
Linguistics. -
電子資源:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30811670
ISBN:
9798382192055
Probabilistic Evaluation of Comparative Reconstructions.
Munteanu, Andrei.
Probabilistic Evaluation of Comparative Reconstructions.
- Ann Arbor : ProQuest Dissertations & Theses, 2024 - 246 p.
Source: Dissertations Abstracts International, Volume: 85-10, Section: A.
Thesis (Ph.D.)--University of Toronto (Canada), 2024.
This item must not be sold to any third party vendors.
This dissertation introduces Wordlist Distortion Theory, a framework for the probabilistic evaluation of comparative reconstructions in historical linguistics. The framework estimates the likelihood that a randomly generated wordlist merits the same type and number of diachronic transformations (e.g. sound changes, replacements, etc.) as required by the reconstruction. This is the first probabilistic evaluation of comparative reconstruction of its kind.Wordlist Distortion Theory is primarily intended as a platform for objective and accessible debate surrounding spurious reconstruction in historical linguistics. Additionally, the framework can be used as a tiebreaker between conflicting reconstructions for the same data. Finally, the framework allows for probability-based theoretical arguments in historical linguistics about the interaction of synchronic and diachronic factors with reconstruction reliability. For example, this dissertation argues that the effect of semantic change on reconstruction reliability is relatively minor and the effect of contrast-preserving sound change almost negligible.Wordlist Distortion Theory can also feature as part of a machine learning algorithm, allowing for the stochastic generation and evaluation of comparative reconstructions. This dissertation presents the results of a case study conducted on 74 Austronesian languages and 5 proto-languages, where, for each pair of language and proto-language, the algorithm suggested sound changes with the goal of decreasing the probability of a random match as calculated by Wordlist Distortion Theory. The resulting reconstructions are in line with general knowledge about sound change and Austronesian historical linguistics. Additionally, Wordlist Distortion Theory was used to evaluate the putative connection between the Austronesian and Ongan language families. Automated reconstructions from Proto-Ongan-Austronesian to members of either family are not conclusive.
ISBN: 9798382192055Subjects--Topical Terms:
524476
Linguistics.
Subjects--Index Terms:
Machine learning
Probabilistic Evaluation of Comparative Reconstructions.
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This dissertation introduces Wordlist Distortion Theory, a framework for the probabilistic evaluation of comparative reconstructions in historical linguistics. The framework estimates the likelihood that a randomly generated wordlist merits the same type and number of diachronic transformations (e.g. sound changes, replacements, etc.) as required by the reconstruction. This is the first probabilistic evaluation of comparative reconstruction of its kind.Wordlist Distortion Theory is primarily intended as a platform for objective and accessible debate surrounding spurious reconstruction in historical linguistics. Additionally, the framework can be used as a tiebreaker between conflicting reconstructions for the same data. Finally, the framework allows for probability-based theoretical arguments in historical linguistics about the interaction of synchronic and diachronic factors with reconstruction reliability. For example, this dissertation argues that the effect of semantic change on reconstruction reliability is relatively minor and the effect of contrast-preserving sound change almost negligible.Wordlist Distortion Theory can also feature as part of a machine learning algorithm, allowing for the stochastic generation and evaluation of comparative reconstructions. This dissertation presents the results of a case study conducted on 74 Austronesian languages and 5 proto-languages, where, for each pair of language and proto-language, the algorithm suggested sound changes with the goal of decreasing the probability of a random match as calculated by Wordlist Distortion Theory. The resulting reconstructions are in line with general knowledge about sound change and Austronesian historical linguistics. Additionally, Wordlist Distortion Theory was used to evaluate the putative connection between the Austronesian and Ongan language families. Automated reconstructions from Proto-Ongan-Austronesian to members of either family are not conclusive.
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https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30811670
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