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 12 of 12 for “"cross-lingual transfer"”.
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Efficient and Composable Adaptation for Cross-Lingual Transfer
… to overfitting, lend them to applications in cross-lingual transfer, where data from "high-resource" source language(s) is employed to improve performance of NLP systems for (typically lower-resource) target languages. For instance, two independently trained PEFT modules, one for a specific …
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Improving Parameter-Efficient Cross-Lingual Transfer for Low-Resource Languages
… data sources to achieve good performance across a range of resource scarcity. In this thesis, this question is addressed from two different perspectives in the context of modular and parameter-efficient approaches to cross-lingual transfer. Firstly, we propose different strategies for …
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Consonant (De)gradation in Ingrian?
… -- a morphological generation task was tested across labeled data encompassing multiple stages of enrichment for the low-resource language Ingrian. Due to limitations in the available data for Ingrian, weighted finite-state transducers (WFSTs) were used to generate an expanded vocabulary via …
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Data-Efficient Bilingual Lexicon Induction with Pretrained Language Models
Bilingual dictionaries are essential language resources that play a crucial role in the development of modern multilingual and cross-lingual natural language processing (NLP) systems, particularly for resource-lean languages. Although there are 7,000+ languages spoken worldwide, existing bilingual …
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Advancing Language Equity and Sample Efficiency in Task-Oriented Dialogue Systems
… majority and minority languages. Equitable multilingual TOD systems should not only be accessible (able to converse with the users in their language) but also useful (addressing specific needs of diverse linguistic communities). This thesis aims to promote language equity in dialogue systems …
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Learning with Limited Labeled Data: Techniques and Applications
… the second problem we focus on self-learning in cross-lingual transfer task. Our goal here is to develop a framework that can make the pretrained cross-lingual model continue learning the knowledge with large amount of unlabeled data. Existing self-learning methods in crosslingual transfer tasks …
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SYMBOLIC AND NEURAL APPROACHES TO NATURAL LANGUAGE INFERENCE
… challenging for neural models, and examines the cross-lingual transfer ability of state-of-the-art multilingual neural models, focusing on Chinese. I collected the first large-scale NLI corpus for Chinese, using a procedure that is superior to what has been done with English, along with four …
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Subword segmental neural language generation for Nguni languages
… tokenisation-based language models, on average across the four Nguni languages. We also evaluate SSLM as an unsupervised morphological segmenter, showing that its learned subwords are closer to morphemes than standard subword tokens. Since SSLM is our first instantiation of subword segmental …
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Grammatical analysis of Maltese text
… looks at grammatical inference from both a mono-lingual perspective as well as a multilingual perspective. Maltese is also a low-resource language, with minimal human-annotated data in grammatical inference. A neural approach is used to train a series of models that are able to take a Maltese …
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Inductive Bias and Modular Design for Sample-Efficient Neural Language Learning
… faculties, combined with the ability to transfer and recombine knowledge across these domains. The main contribution of my thesis is giving concrete form to both these intuitions. Firstly, I argue that endowing a neural network with the correct inductive biases is equivalent to …
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Speech Foundation Models for Audio Processing
… such as Whisper have shown strong performance across a variety of audio processing tasks, including automatic speech recognition (ASR) and speech translation. Unlike traditional systems that require task-specific architectures and extensive supervision, these models offer a unified and flexible …
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Speech recognition with probabilistic transcriptions and end-to-end systems using deep learning
… contributions of this thesis are the following: Cross-Lingual Speech Recognition in Under-Resourced Scenarios: A well-resourced language is a language with an abundance of resources to support the development of speech technology. Those resources are usually defined in terms of 100+ hours of …