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 15 of 15 for “"language technology"”.
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USE OF LANGUAGE TECHNOLOGY TO IMPROVE MATCHING AND RETRIEVAL IN TRANSLATION MEMORY
Current Translation Memory (TM) tools lack semantic knowledge while matching. Most TM tools compute similarity at the string level, which does not take into account semantic aspects in matching. Therefore, semantically similar segments, which differ on the surface form, are often not retrieved. In …
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On internal language representations in deep learning : an analysis of machine translation and speech recognition
Language technology has become pervasive in everyday life. Neural networks are a key component in this technology thanks to their ability to model large amounts of data. Contrary to traditional systems, models based on deep neural networks (a.k.a. deep learning) can be trained in an end-to-end …
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Effective automatic speech recognition data collection for under–resourced languages
… transcribed speech corpora for under-resourced languages plays a pivotal role in developing automatic speech recognition (ASR) technologies for such languages, a key step in developing these technologies is the effective collection of ASR data, consisting of transcribed audio and associated meta …
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Self-Supervised Learning for Speech Processing
… remarkable performance on various spoken language processing applications, often being the state of the arts on the corresponding leaderboards. However, the fact that training these systems relies on large amounts of annotated speech poses a scalability bottleneck for the continued …
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Adapting existing games for education using speech recognition
… practice of other skills. Incorporating spoken language technology could make it possible for users to learn as they play, keeping up with game speed through multimodal interaction. Two challenges exist in this research: first, it is unclear which learning strategy would be most eective when …
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Inductive Bias and Modular Design for Sample-Efficient Neural Language Learning
Most of the world's languages suffer from the paucity of annotated data. This curbs the effectiveness of supervised learning, the most widespread approach to modelling language. Instead, an alternative paradigm could take inspiration from the propensity of children to acquire language from limited …
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The effects of part–of–speech tagging on text–to–speech synthesis for resource–scarce languages
In the world of human language technology, resource-scarce languages (RSLs) suffer from the problem of little available electronic data and linguistic expertise. The Lwazi project in South Africa is a large-scale endeavour to collect and apply such resources for all eleven of the official South …
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Chinese typewriters speak: the political power of writing machines in 20th-century China
… developing a typing system for a character-based language was an enormously complex challenge, leading to the creation of a wide range of typing machines and systems. A remarkably diverse group of prominent figures in the 20th century, including social activists, businessmen, statesmen, literary …
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Neural Dependency Parsing of Informal Persian
… corpora, and computational models of this language focus mainly on the formal variant.In this dissertation, I present the phonological, morphological, and syntactic distinctions between formal and informal Persian, showing that these two variants have fundamental differences that cannot be …
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Named entity recognition for Icelandic: comparing and combining different machine learning methods
… NER is often an important step in other Natural Language Processing tasks, like in question answering or machine translation. NER is a subtask of Information Extraction. A neural model for NER has already been implemented for Icelandic (NeuroNER), but this is as far as we know, the only previous …
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Speech-Based Emotion Modelling and Mental Disorder Detection
Emotion modelling and understanding are crucial for artificial intelligence (AI) systems to achieve enhanced contextual understanding and adaptive, personalised human-AI interaction. Speech contains important clues for detecting emotion through a variety of vocal characteristics such as prosody, …
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Improving Automated Literature-based Discovery with Neural Networks: Neural biomedical Named Entity Recognition, Link Prediction and Discovery
… of ranked outputs. Recent advances in Natural Language Processing (NLP) allow for deep textual analysis to obtain a wide coverage of information present in text and can adapt easily to recognising new biomedical entities and terms. Similarly, recent advances in graph processing have made it …
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Decoding Relations between Geopolitical Risk and Financial Markets
This thesis examines the relationship between geopolitical risk and financial markets by analyzing two major geopolitical events: the Russia-Ukraine conflict and China-related tensions. Using Latent Dirichlet Allocation (LDA) topic modeling, it identifies key topics discussed in business media. …
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La il·lusió-miratge: de l'anhel de felicitat a la desorientació del jo
La conquesta de la felicitat s'ha convertit en el pal de paller del llenguatge familiar i social. Impregna la tanca publicitària i mou el molí gegantí de l'economia. Els anuncis llampants del tecnològic dibuixen una sinuosa ruta cap a un estat feliç. Una pretensió aliena i externa als subjectes, …
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Instructor Views about the Use of Technology in Teaching ESL Writing at the University Level
<p>The presence of technology in education has affected how the process of teaching and learning of ESL writing occurs. In ESL composition courses at the university level, technology as a pedagogical tool has become common among instructors and the use of technology in ESL composition instruction …