Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 10 of 10 for “"grammatical error correction"”.
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Automatic annotation of error types for grammatical error correction
Grammatical Error Correction (GEC) is the task of automatically detecting and correcting grammatical errors in text. Although previous work has focused on developing systems that target specific error types, the current state of the art uses machine translation to correct all error types …
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The Roles of Language Models and Hierarchical Models in Neural Sequence-to-Sequence Prediction
… checkers and morphology databases help neural grammatical error correction. We also focus on language models that often do not play a role in vanilla end-to-end approaches and apply them in different ways to word reordering, grammatical error correction, low-resource NMT, and document-level …
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Investigating Interlingual Errors to Enhance Intelligent Writing Assistants for Second Language Learners
… through explanatory messages in response to grammatical errors found in a given piece of text. These AWAs have been built upon advances in machine learning (ML) and natural language processing (NLP) for state-of-the-art grammatical error correction and feedback capabilities, as well as …
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Automatic Assessment of L2 Spoken English
… feedback explored in this thesis are feedback on grammatical accuracy and assessment related to particular aspects of proficiency (e.g., grammar, pronunciation, rhythm, fluency, etc.). The first study explores the use of written data and the impact of features extracted through grammatical error …
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Speech Foundation Models for Audio Processing
… This thesis begins by addressing ASR error correction, a task that aims to refine ASR outputs to improve the accuracy and readability of transcriptions. Traditional approaches typically take the 1-best ASR hypothesis as input, which restricts correction models to the limited context of …
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Non-native text analysis with Syntactic Diff, a general comparative text mining framework
… which in turn generates a need for grammar correction and analysis. Even aside from MOOCs, the number of English learners only in Asia alone is in the tens of millions. In response to this powerful motivation, we describe SYNTACTIC DIFF, a novel edit-based method for transforming sequences …
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Adversarial Attacks on Natural Language and Speech Processing Models
… tasks such as Neural Machine Translation and Grammatical Error Correction. Further discussions focus on the use of an automated scoring module that operates on output sequences in the perception-based framework. It is shown that if powerful LLMs (such as ChatGPT) are leveraged for this scoring …
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Improving Cascaded Systems in Spoken Language Processing
… be made at the upstream modules, and early stage errors would potentially propagate through and degrade the downstream modules. Furthermore, individual modules in the cascaded system are often trained in their corresponding domains, which can be different from the target domain of the spoken …
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Automated methods for text correction
Development of automatic text correction systems has a long history in natural language processing research. This thesis considers the problem of correcting writing mistakes made by non-native English speakers. We address several types of errors commonly exhibited by non-native English writers – …