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Dissertations / Theses on the topic 'Language models'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Livingstone, Daniel Jack. "Computer models of the evolution of language and languages." Thesis, University of the West of Scotland, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.398331.

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2

Laurençon, Hugo. "Foundation Vision-Language models." Electronic Thesis or Diss., Sorbonne université, 2025. http://www.theses.fr/2025SORUS004.

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Ces dernières années, les grands modèles de langage (LLMs) ont montré des performances remarquables sur des tâches variées et ont commencé à être largement intégrés dans diverses applications. Les modèles vision-langage (VLMs), qui étendent les LLMs en incorporant en plus la compréhension d'images, offrent un potentiel supplémentaire. Ces modèles pourraient transformer des domaines tels que le développement web en traduisant des captures d'écran de pages web en code, faciliter la recherche d'informations via une navigation web autonome, et automatiser des tâches comme la classification et la s

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3

Ryder, Robin Jeremy. "Phylogenetic models of language diversification." Thesis, University of Oxford, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.543009.

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4

Waegner, Nicholas Paul. "Stochastic models for language acquisition." Thesis, University of Cambridge, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.309214.

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5

Niesler, Thomas Richard. "Category-based statistical language models." Thesis, University of Cambridge, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.627372.

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6

Wallach, Hanna Megan. "Structured topic models for language." Thesis, University of Cambridge, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.612547.

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7

Douzon, Thibault. "Language models for document understanding." Electronic Thesis or Diss., Lyon, INSA, 2023. http://www.theses.fr/2023ISAL0075.

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Chaque jour, les entreprises du monde entier reçoivent et traitent d'énormes volumes de documents, entraînant des coûts considérables. Pour réduire ces coûts, de grandes entreprises automatisent le traitement documentaire, visant une automatisation complète. Cette thèse se concentre sur l'utilisation de modèles d'apprentissage machine pour extraire des informations de documents. Les progrès récents en matière d'architecture de modèle, en particulier les transformeurs, ont révolutionné le domaine grâce à leur utilisation généralisée de l'attention et à l'amélioration des pré-entraînements auto-

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8

Townsend, Duncan Clarke McIntire. "Using a symbolic language parser to Improve Markov language models." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/100621.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 31-32).<br>This thesis presents a hybrid approach to natural language processing that combines an n-gram (Markov) model with a symbolic parser. In concert these two techniques are applied to the problem of sentence simplific

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9

Buttery, P. J. "Computational models for first language acquisition." Thesis, University of Cambridge, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.597195.

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This work investigates a computational model of first language acquisition; the Categorical Grammar Learner or CGL. The model builds on the work of Villavicenio, who created a parametric Categorical Grammar learner that organises its parameters into an inheritance hierarchy, and also on the work of Buszkowski and Kanazawa, who demonstrated the learnability of a <i>k</i>-valued Classic Categorial Grammar (which uses only the rules of function application) from strings. The CGL is able to learn a <i>k</i>-valued General Categorial Grammar (which uses the rules of function application, function c

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10

Nkadimeng, Calvin. "Language identification using Gaussian mixture models." Thesis, Stellenbosch : University of Stellenbosch, 2010. http://hdl.handle.net/10019.1/4170.

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Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2010.<br>ENGLISH ABSTRACT: The importance of Language Identification for African languages is seeing a dramatic increase due to the development of telecommunication infrastructure and, as a result, an increase in volumes of data and speech traffic in public networks. By automatically processing the raw speech data the vital assistance given to people in distress can be speeded up, by referring their calls to a person knowledgeable in that language. To this effect a speech corpus was developed and various

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11

Schuster, Ingmar. "Probabilistic models of natural language semantics." Doctoral thesis, Universitätsbibliothek Leipzig, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-204503.

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This thesis tackles the problem of modeling the semantics of natural language. Neural Network models are reviewed and a new Bayesian approach is developed and evaluated. As the performance of standard Monte Carlo algorithms proofed to be unsatisfactory for the developed models, the main focus lies on a new adaptive algorithm from the Sequential Monte Carlo (SMC) family. The Gradient Importance Sampling (GRIS) algorithm developed in the thesis is shown to give very good performance as compared to many adaptive Markov Chain Monte Carlo (MCMC) algorithms on a range of complex target distributions

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12

Damljanovic, Danica. "Natural language interfaces to conceptual models." Thesis, University of Sheffield, 2011. http://etheses.whiterose.ac.uk/1630/.

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Accessing structured data in the form of ontologies currently requires the use of formal query languages (e.g., SeRQL or SPARQL) which pose significant difficulties for non-expert users. One way to lower the learning overhead and make ontology queries more straightforward is through a Natural Lan- guage Interface (NLI). While there are existing NLIs to structured data with reasonable performance, they tend to require expensive customisation to each new domain. Additionally, they often require specific adherence to a pre-defined syntax which, in turn, means that users still have to undergo trai

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13

Delmestri, Antonella. "Data Driven Models for Language Evolution." Doctoral thesis, Università degli studi di Trento, 2011. https://hdl.handle.net/11572/368357.

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Natural languages that originate from a common ancestor are genetically related, words are the core of any language and cognates are words sharing the same ancestor and etymology. Cognate identification, therefore, represents the foundation upon which the evolutionary history of languages may be discovered, while linguistic phylogenetic inference aims to estimate the genetic relationships that exist between them. In this thesis, using several techniques originally developed for biological sequence analysis, we have designed a data driven orthographic learning system for measuring string simila

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14

Delmestri, Antonella. "Data Driven Models for Language Evolution." Doctoral thesis, University of Trento, 2011. http://eprints-phd.biblio.unitn.it/473/1/PhD-Thesis_Uploaded.pdf.

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Natural languages that originate from a common ancestor are genetically related, words are the core of any language and cognates are words sharing the same ancestor and etymology. Cognate identification, therefore, represents the foundation upon which the evolutionary history of languages may be discovered, while linguistic phylogenetic inference aims to estimate the genetic relationships that exist between them. In this thesis, using several techniques originally developed for biological sequence analysis, we have designed a data driven orthographic learning system for measuring string simil

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15

Miao, Yishu. "Deep generative models for natural language processing." Thesis, University of Oxford, 2017. http://ora.ox.ac.uk/objects/uuid:e4e1f1f9-e507-4754-a0ab-0246f1e1e258.

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Deep generative models are essential to Natural Language Processing (NLP) due to their outstanding ability to use unlabelled data, to incorporate abundant linguistic features, and to learn interpretable dependencies among data. As the structure becomes deeper and more complex, having an effective and efficient inference method becomes increasingly important. In this thesis, neural variational inference is applied to carry out inference for deep generative models. While traditional variational methods derive an analytic approximation for the intractable distributions over latent variables, here

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16

Morganti, Caroline (Caroline Taylor). "Applying natural language models and causal models to project management systems." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/119577.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 97-101).<br>This thesis concerns itself with two problems. First, it examines ways in which to use natural language features in time-varying data in predictive models, specifically applied to the problem of software project

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17

Rodrigeuz-Sanchez, I. "Matrix models of second language vocabulary acquisition." Thesis, Swansea University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.638702.

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Most of the current research in L2 vocabulary acquisition has been too focused on what it is to learn a word, and has neglected how whole vocabularies grow or decline. In general, it is assumed that vocabulary gains and losses are incremental and follow a linear progression. This thesis postulates a model which considers several discrete stages of knowledge and accounts for the unstable nature of vocabulary knowledge, where words can change from one state to any other. Matrix algebra is a tool capable to operate with such a model and produce long-term forecasts of vocabulary size. Our experime

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18

Lei, Tao Ph D. Massachusetts Institute of Technology. "Interpretable neural models for natural language processing." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/108990.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 109-119).<br>The success of neural network models often comes at a cost of interpretability. This thesis addresses the problem by providing justifications behind the model's structure and predictions. In the first part of this thesis, we present a class of sequence operations for text processing. The proposed component generalizes from convolution operations and gated aggregations. As justi

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19

Kunz, Jenny. "Neural Language Models with Explicit Coreference Decision." Thesis, Uppsala universitet, Institutionen för lingvistik och filologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-371827.

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Coreference is an important and frequent concept in any form of discourse, and Coreference Resolution (CR) a widely used task in Natural Language Understanding (NLU). In this thesis, we implement and explore two recent models that include the concept of coreference in Recurrent Neural Network (RNN)-based Language Models (LM). Entity and reference decisions are modeled explicitly in these models using attention mechanisms. Both models learn to save the previously observed entities in a set and to decide if the next token created by the LM is a mention of one of the entities in the set, an entit

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20

Davis, Alexandre Guelman. "Subject classification through context-enriched language models." Universidade Federal de Minas Gerais, 2015. http://hdl.handle.net/1843/ESBF-9VKK2Q.

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Throughout the years, humans have developed a complex and intricate system of communication with several means of conveying information that range from books, newspapers and television to, more recently, social media. However, efficiently retrieving and understanding messages from social media for extracting useful information is challenging, especially considering that shorter messages are strongly dependent on context. Users often assume that their social media audience is aware of the associated background and the underlying real world events. This allows them to shorten their messages with

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21

Pérez-Sancho, Carlos. "Stochastic language models for music information retrieval." Doctoral thesis, Universidad de Alicante, 2009. http://hdl.handle.net/10045/14217.

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22

Labeau, Matthieu. "Neural language models : Dealing with large vocabularies." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS313/document.

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Le travail présenté dans cette thèse explore les méthodes pratiques utilisées pour faciliter l'entraînement et améliorer les performances des modèles de langues munis de très grands vocabulaires. La principale limite à l'utilisation des modèles de langue neuronaux est leur coût computationnel: il dépend de la taille du vocabulaire avec laquelle il grandit linéairement. La façon la plus aisée de réduire le temps de calcul de ces modèles reste de limiter la taille du vocabulaire, ce qui est loin d'être satisfaisant pour de nombreuses tâches. La plupart des méthodes existantes pour l'entraînement

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23

Bayer, Ali Orkan. "Semantic Language models with deep neural Networks." Doctoral thesis, Università degli studi di Trento, 2015. https://hdl.handle.net/11572/367784.

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Spoken language systems (SLS) communicate with users in natural language through speech. There are two main problems related to processing the spoken input in SLS. The first one is automatic speech recognition (ASR) which recognizes what the user says. The second one is spoken language understanding (SLU) which understands what the user means. We focus on the language model (LM) component of SLS. LMs constrain the search space that is used in the search for the best hypothesis. Therefore, they play a crucial role in the performance of SLS. It has long been discussed that an improvement in the

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Bayer, Ali Orkan. "Semantic Language models with deep neural Networks." Doctoral thesis, University of Trento, 2015. http://eprints-phd.biblio.unitn.it/1578/1/bayer_thesis.pdf.

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Spoken language systems (SLS) communicate with users in natural language through speech. There are two main problems related to processing the spoken input in SLS. The first one is automatic speech recognition (ASR) which recognizes what the user says. The second one is spoken language understanding (SLU) which understands what the user means. We focus on the language model (LM) component of SLS. LMs constrain the search space that is used in the search for the best hypothesis. Therefore, they play a crucial role in the performance of SLS. It has long been discussed that an improvement in the

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25

Yang, Xi. "Discriminative acoustic and sequence models for GMM based automatic language identification /." View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?ECED%202007%20YANG.

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26

Scarcella, Alessandro. "Recurrent neural network language models in the context of under-resourced South African languages." Master's thesis, University of Cape Town, 2018. http://hdl.handle.net/11427/29431.

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Over the past five years neural network models have been successful across a range of computational linguistic tasks. However, 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 evaluate the implications of recent advances in neural network language modelling techniques for under-resourced South African languages. Rudimentary, single layered recurrent neural n

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27

Takeda, Koichi. "Building Natural Language Processing Applications Using Descriptive Models." 京都大学 (Kyoto University), 2010. http://hdl.handle.net/2433/120372.

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28

Henter, Gustav Eje. "Probabilistic Sequence Models with Speech and Language Applications." Doctoral thesis, KTH, Kommunikationsteori, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-134693.

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Series data, sequences of measured values, are ubiquitous. Whenever observations are made along a path in space or time, a data sequence results. To comprehend nature and shape it to our will, or to make informed decisions based on what we know, we need methods to make sense of such data. Of particular interest are probabilistic descriptions, which enable us to represent uncertainty and random variation inherent to the world around us. This thesis presents and expands upon some tools for creating probabilistic models of sequences, with an eye towards applications involving speech and language.

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29

Lou, Bill Pi-ching. "New models of natural language for automated assessment." Thesis, University of Nottingham, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.337661.

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30

Gwei, G. M. "New models of natural language for consultative computing." Thesis, University of Nottingham, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.378986.

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31

McCandless, Michael Kyle. "Automatic acquisition of language models for speech recognition." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/36462.

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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.<br>Includes bibliographical references (leaves 138-141).<br>by Michael Kyle McCanless.<br>M.S.

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Brorson, Erik. "Classifying Hate Speech using Fine-tuned Language Models." Thesis, Uppsala universitet, Statistiska institutionen, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-352637.

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Given the explosion in the size of social media, the amount of hate speech is also growing. To efficiently combat this issue we need reliable and scalable machine learning models. Current solutions rely on crowdsourced datasets that are limited in size, or using training data from self-identified hateful communities, that lacks specificity. In this thesis we introduce a novel semi-supervised modelling strategy. It is first trained on the freely available data from the hateful communities and then fine-tuned to classify hateful tweets from crowdsourced annotated datasets. We show that our model

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33

Li, Zhongliang. "Slim Embedding Layers for Recurrent Neural Language Models." Wright State University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=wright1531950458646138.

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34

Shao, Han. "Pretraining Deep Learning Models for Natural Language Understanding." Oberlin College Honors Theses / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=oberlin158955297757398.

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35

Tripodi, Rocco <1982&gt. "Evolutionary game theoretic models for natural language processing." Doctoral thesis, Università Ca' Foscari Venezia, 2015. http://hdl.handle.net/10579/8351.

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This thesis is aimed at discovering new learning algorithms inspired by principles of biological evolution, which are able to exploit relational and contextual information, viewing clustering and classification problems in a dynamical system perspective. In particular, we have investigated how game theoretic models can be used to solve different Natural Language Processing tasks. Traditional studies of language have used a game-theoretic perspective to study how language evolves over time and how it emerges in a community but to the best of our knowledge, this is the first attempt to use game-

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36

Zausa, Giulio <1998&gt. "Exploiting Language Models for Vector-Style Images Synthesis." Master's Degree Thesis, Università Ca' Foscari Venezia, 2021. http://hdl.handle.net/10579/19965.

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Deep learning generative models have been successfully applied to synthesize images from various sources, like human faces and natural images, with impressive and realistic results. Nonetheless, not much work has been done for generating icons and vector-style images since synthesizing them requires precision and high-frequency details. Such images are essential for modern software and web development since they communicate concepts faster and more universally. We try to fill the gap by proposing an explicit density conditional generative model that can yield high-resolution samples when train

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Meynard, Barthélémy. "Language Models towards Conditional Generative Modelsof Proteins Sequences." Electronic Thesis or Diss., Sorbonne université, 2024. http://www.theses.fr/2024SORUS195.

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Nous commençons par examiner ce qui rend un modèle génératif efficace pour les séquences de protéines. Dans notre première étude, "Interpretable Pairwise Distillations for Generative Protein Sequence Models" nous comparons les modèles de réseaux de neurones complexes à des modèles de distributions pair à pair plus simples. Cette comparaison révèle que les modèles plus simples peuvent égaler de près la performance des modèles plus complexes dans la prédiction de l'effet des mutations sur les protéines. Cette découverte remet en question l'hypothèse selon laquelle les modèles plus complexes sont

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González, Jorge, and Francisco Casacuberta. "Phrase-based finite state models." Universität Potsdam, 2008. http://opus.kobv.de/ubp/volltexte/2008/2720/.

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In the last years, statistical machine translation has already demonstrated its usefulness within a wide variety of translation applications. In this line, phrase-based alignment models have become the reference to follow in order to build competitive systems. Finite state models are always an interesting framework because there are well-known efficient algorithms for their representation and manipulation. This document is a contribution to the evolution of finite state models towards a phrase-based approach. The inference of stochastic transducers that are based on bilingual phrases is carefu

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Correia, Filipe André Sobral. "Model morphisms (MoMo) to enable language independent information models and interoperable business networks." Master's thesis, Faculdade de Ciências e Tecnologia, 2010. http://hdl.handle.net/10362/4782.

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MSc. Dissertation presented at Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa to obtain the Master degree in Electrical and Computer Engineering<br>With the event of globalisation, the opportunities for collaboration became more evident with the effect of enlarging business networks. In such conditions, a key for enterprise success is a reliable communication with all the partners. Therefore, organisations have been searching for flexible integrated environments to better manage their services and product life cycle, where their software applications could be easily integrat

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Cortez, Marc. "Models, metaphors, and multivalent contextualizations religious language and the nature of contextual theology /." Online full text .pdf document, available to Fuller patrons only, 2004. http://www.tren.com.

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Wik, Preben. "The Virtual Language Teacher : Models and applications for language learning using embodied conversational agents." Doctoral thesis, KTH, Tal-kommunikation, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-33579.

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This thesis presents a framework for computer assisted language learning using a virtual language teacher. It is an attempt at creating, not only a new type of language learning software, but also a server-based application that collects large amounts of speech material for future research purposes.The motivation for the framework is to create a research platform for computer assisted language learning, and computer assisted pronunciation training.Within the thesis, different feedback strategies and pronunciation error detectors are exploredThis is a broad, interdisciplinary approach, combinin

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Hadi, Abdine. "Leveraging Transformer-Based Language Models to Bridge the Gap Between Language and Specialized Domains." Electronic Thesis or Diss., Institut polytechnique de Paris, 2024. http://www.theses.fr/2024IPPAX020.

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L'ère des modèles de langage basés sur des 'transormers' a ouvert la voie à un nouveau paradigme dans le traitement du langage naturel (NLP), permettant des performances remarquables dans un large éventail de tâches dans les domaines de la compréhension du langage naturel (NLU) et de la génération du langage naturel (NLG). Cette thèse se penche sur le potentiel de transformation des modèles de langage basés sur les 'transformers' lorsqu'ils sont appliqués à des domaines et des langues spécialisés. Elle comprend quatre projets de recherche, chacun contribuant à l'objectif global d'amélioration

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Ana, Knežević. "Primena panel modela u identifikovanju faktora uspešnosti poslovanja proizvodnih preduzeća." Phd thesis, Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, 2015. http://www.cris.uns.ac.rs/record.jsf?recordId=95568&source=NDLTD&language=en.

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Osnovni cilj istraživanja predstavlja identifikovanje faktorakoji utiču na uspešnost poslovanja proizvodnih preduzeća, i tokorišćenjem metodologije iz oblasti analize panel podataka.Kao mera uspešnosti poslovanja korišćena je profitabilnost.Istraživanjem je obuhvaćena analiza uticaja nekoliko internih ieksternih faktora. Utvrđen je značajan uticaj kako internih(veličina preduzeća, finansijska zaduženost, efikasnostkorišćenja imovine i stopa opipljivosti imovine) tako ieksternih (inflacija, BDP i kamatne stope) faktora nauspešnost poslovanja proizvodnih preduzeća.<br>The main goal of this resea

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Dillehay, Tom D. "Andean Language and Archaeology: A Final Comment." Pontificia Universidad Católica del Perú, 2012. http://repositorio.pucp.edu.pe/index/handle/123456789/113367.

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45

Konstas, Ioannis. "Joint models for concept-to-text generation." Thesis, University of Edinburgh, 2014. http://hdl.handle.net/1842/8926.

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Much of the data found on the world wide web is in numeric, tabular, or other nontextual format (e.g., weather forecast tables, stock market charts, live sensor feeds), and thus inaccessible to non-experts or laypersons. However, most conventional search engines and natural language processing tools (e.g., summarisers) can only handle textual input. As a result, data in non-textual form remains largely inaccessible. Concept-to-text generation refers to the task of automatically producing textual output from non-linguistic input, and holds promise for rendering non-linguistic data widely access

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Amato, Roberta. "Human collective behavior models: language, cooperation and social conventions." Doctoral thesis, Universitat de Barcelona, 2018. http://hdl.handle.net/10803/565420.

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The topics dealt with in this thesis are all part of the general problem of social consensus, namely how a convention flourish and decay and what motivates people to conform to it. Examples range from driving on the right side of the street, to language, rules of courtesy or moral judgments. Some conventions arise directly from the need to coordinate or conform, such as fashion or speaking the same language, others, instead, apply to situations where there is a tension between individual and collective interest, such as cooperation, reciprocity, etc. This thesis is developed around three ma

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Clarkson, P. R. "Adaptation of statistical language models for automatic speech recognition." Thesis, University of Cambridge, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.597745.

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Statistical language models encode linguistic information in such a way as to be useful to systems which process human language. Such systems include those for optical character recognition and machine translation. Currently, however, the most common application of language modelling is in automatic speech recognition, and it is this that forms the focus of this thesis. Most current speech recognition systems are dedicated to one specific task (for example, the recognition of broadcast news), and thus use a language model which has been trained on text which is appropriate to that task. If, ho

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黃伯光 and Pak-kwong Wong. "Statistical language models for Chinese recognition: speech and character." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31239456.

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Mukherjee, Niloy 1978. "Spontaneous speech recognition using visual context-aware language models." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/62380.

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Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2003.<br>Includes bibliographical references (p. 83-88).<br>The thesis presents a novel situationally-aware multimodal spoken language system called Fuse that performs speech understanding for visual object selection. An experimental task was created in which people were asked to refer, using speech alone, to objects arranged on a table top. During training, Fuse acquires a grammar and vocabulary from a "show-and-tell" procedure in which visual scenes are paired with v

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Lin, Chun Hung. "Automatic Question Generation with Pre-trained Masked Language Models." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-289559.

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In this project, we study the task of generating a question from a given passage-answer pair using pre-trained masked language models. Asking questions is of importance in artificial intelligence development because it makes a machine look intelligent when it raises a reasonable and well-constructed question. Also, question generation has its applications such as drafting questions for a reading comprehension test and augmenting data for expanding the training set of a question answering task. We focus on using pre-trained masked language models throughout this project. Masked language modelin

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