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Full-Text Articles in Computational Linguistics

Emergent Typological Effects Of Agent-Based Learning Models In Maximum Entropy Grammar, Coral Hughto Dec 2020

Emergent Typological Effects Of Agent-Based Learning Models In Maximum Entropy Grammar, Coral Hughto

Doctoral Dissertations

This dissertation shows how a theory of grammatical representations and a theory of learning can be combined to generate gradient typological predictions in phonology, predicting not only which patterns are expected to exist, but also their relative frequencies: patterns which are learned more easily are predicted to be more typologically frequent than those which are more difficult. In Chapter 1 I motivate and describe the specific implementation of this methodology in this dissertation. Maximum Entropy grammar (Goldwater & Johnson 2003) is combined with two agent-based learning models, the iterated and the interactive learning model, each of which mimics a type …


Computational Approaches To The Syntax–Prosody Interface: Using Prosody To Improve Parsing, Hussein M. Ghaly Feb 2020

Computational Approaches To The Syntax–Prosody Interface: Using Prosody To Improve Parsing, Hussein M. Ghaly

Dissertations, Theses, and Capstone Projects

Prosody has strong ties with syntax, since prosody can be used to resolve some syntactic ambiguities. Syntactic ambiguities have been shown to negatively impact automatic syntactic parsing, hence there is reason to believe that prosodic information can help improve parsing. This dissertation considers a number of approaches that aim to computationally examine the relationship between prosody and syntax of natural languages, while also addressing the role of syntactic phrase length, with the ultimate goal of using prosody to improve parsing.

Chapter 2 examines the effect of syntactic phrase length on prosody in double center embedded sentences in French. Data collected …


Phonologically-Informed Speech Coding For Automatic Speech Recognition-Based Foreign Language Pronunciation Training, Anthony J. Vicario Feb 2020

Phonologically-Informed Speech Coding For Automatic Speech Recognition-Based Foreign Language Pronunciation Training, Anthony J. Vicario

Dissertations, Theses, and Capstone Projects

Automatic speech recognition (ASR) and computer-assisted pronunciation training (CAPT) systems used in foreign-language educational contexts are often not developed with the specific task of second-language acquisition in mind. Systems that are built for this task are often excessively targeted to one native language (L1) or a single phonemic contrast and are therefore burdensome to train. Current algorithms have been shown to provide erroneous feedback to learners and show inconsistencies between human and computer perception. These discrepancies have thus far hindered more extensive application of ASR in educational systems.

This thesis reviews the computational models of the human perception of American …


Pmkns For Pie: Parsed Morphological Katr Networks Of Sanskrit For Proto-Indo-European, Ryan Mark Mcdonald Jan 2020

Pmkns For Pie: Parsed Morphological Katr Networks Of Sanskrit For Proto-Indo-European, Ryan Mark Mcdonald

Theses and Dissertations--Linguistics

In this thesis, I construct two computational networks for Sanskrit to test theories of nominal accentuation as a way of examining the simplicity of each theory. I will be examining the Paradigmatic Approach and the Compositional Approach to nominal accentuation. For the Paradigmatic Approach, nominals are categorized into mobile and static categories based on how the accent appears in the paradigm (Fortson 2010). For the Compositional Approach, accent mobility is a result of the combination of morphemes and their inherent accent states (Kirparsky 2010). To construct these networks, I use the KATR extension to the DATR language for lexical knowledge …