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.
Results
Showing 1 to 20 of 30 for “"language modelling"”.
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Using Co-evolutionary Information to Improve Protein Language Modelling
… information. We also develop an unsupervised language model that conditions the target sequence on its multiple sequence alignment, allowing us to better model protein families.
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Using document clustering and language modelling in mediated information retrieval.
… hypothesis. We also look at the ability of language models to convey content, to represent topics and to highlight specific concepts in a given context. They are also successfully applied to generate flexible, task-dependent cluster representatives for supporting exploration through browsing …
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Improving searchability of automatically transcribed lectures through dynamic language modelling
Recording university lectures through lecture capture systems is increasingly common. However, a single continuous audio recording is often unhelpful for users, who may wish to navigate quickly to a particular part of a lecture, or locate a specific lecture within a set of recordings. A transcript …
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Improving Searchability of Automatically Transcribed Lectures Through Dynamic Language Modelling
… navigating within recordings, the lexicon and language model used by the ASR engine may be dynamically adapted for the topic of each lecture. A prototype is presented which uses the English Wikipedia as a semantically dense, large language corpus to generate a custom lexicon and language model …
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A statistical approach to language modelling for the ATIS problem
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.
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Deep Learning Based Proteomic Language Modelling for in-silico Protein Generation
A protein is a biopolymer of amino acids that encodes a particular function. Given that there are 20 amino acids possible at each site, even a short protein of 100 amino acids has $20^{100}$ possible variants, making it unrealistic to evaluate all possible sequences in sequence level space. This …
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Dual Fixed-Size Ordinally Forgetting Encoding (FOFE) For Natural Language Processing
… ordinally-forgetting encoding (FOFE) on Natural Language Processing (NLP) tasks, called dual-FOFE. The main idea behind dual-FOFE is that it allows the encoding to be done with two different forgetting factors; this would resolve the original FOFEs dilemma in choosing between the benefits offered …
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Probability models for information retrieval based on divergence from randomness
… discussed and used through-out the thesis. The language modelling approach and the standard probabilistic model are studied under the same foundational view and are experimentally compared to the divergence-from-randomness approach. In revisiting the main information retrieval models in the …
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Towards a Deeper Understanding of Neural Language Generation
In recent years, the field of language modelling has witnessed exciting developments. Especially, thanks to large-scale data, powerful model architectures, and high-speed parallel computing devices, researchers are able to train language models which can generate realistic text. However, our …
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Recurrent neural network language models in the context of under-resourced South African languages
… these triumphs have been concentrated in languages with significant resources such as large datasets. Thus, many languages, which are commonly referred to as under-resourced languages, have received little attention and have yet to benefit from recent advances. This investigation aims to …
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Structure and geometry in sequence-processing neural networks
… neural models on various natural language processing (NLP) tasks has spurred interest in understanding their representation space. In the following chapters we will use various techniques of representational analysis to understand the nature of neural-network based language …
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Improving neural language models on low-resource creole languages
When using neural models for NLP tasks, like language modelling, it is difficult to utilize a language with little data, also known as a low-resource language. Creole languages are frequently low-resource and as such it is difficult to train neural language models for them well. Creole languages …
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Data-driven Materials Informatics for Optoelectronics: From Natural Language Processing to Predictive Modelling of TADF Molecules
… fluorescence. Chapter 2 reviews the natural language processing techniques and language modelling methods that were used throughout the thesis. Chapter 3 demonstrates a pipeline for the extraction of four organic TADF molecule property data from the literature, namely, maximum emission …
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Using Language Models to Understand Molecular Structures
… the imperative need to leverage advances in language modelling to improve machine learning techniques for life sciences. This thesis details research in two such directions, information extraction and text retrieval. Information extraction from chemistry literature is vital for constructing …
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Speaker Dependent Voice Recognition with Word-Tense Association and Part-of-Speech Tagging
… deals with speaker recognition and natural language processing. The most common speaker recognition systems are Text-Dependent and identify the speaker after a key word/phrase is uttered. This thesis presents Text-Independent Speaker recognition systems that incorporate the collaborative …
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The construction and evaluation of statistical models of melodic structure in music perception and composition
… in three stages. First, a number of statistical modelling techniques drawn from the fields of data compression, statistical language modelling and machine learning are subjected to empirical evaluation in the context of sequential prediction of pitch structure in unseen melodies. This …
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Subword segmental neural language generation for Nguni languages
… designed for a limited number of high-resource languages. These advances are not directly applicable to low-resource languages with distinctive linguistic characteristics. In this thesis we develop text generation models for the Nguni languages of South Africa -- isiXhosa, isiZulu, isiNdebele, …
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Beyond pre-training: continual learning and hallucinations in transformer-based language models.
… models have become the norm for various language modelling tasks from document similarity analysis and text classification to natural language generation. Despite the impressive performance on benchmark datasets, adopting pretrained models for real-world applications often requires …
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On the evaluation and application of neural language models for grammatical error detection
Neural language models (NLM) have become a core component in many downstream applications within the field of natural language processing, including the task of data-driven automatic grammatical error detection (GED). This thesis explores whether information from NLMs can positively transfer to GED …
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Noisy language modeling framework using neural network techniques
… research develops a novel intermediate layer language modeling framework called ALMIL (i. e. Adaptive Language Modelling Intermediate Layer) which is seen as a communication language layer between human and computer to analyze noisy language stream and provide users with two fundamental …
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