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 16 of 16 for “"Word Prediction"”.
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Word prediction in assistive technologies for Aphasia rehabilitation in using Systemic Functional Grammar
… by aphasia. What follows is a description of a word prediction strategy based on Systemic Functional Grammar, which incorporates syntactic and contextual analysis; and its potential for aiding language production in assistive technologies</p>
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Curb Cuts for Writing: Students with Learning Disabilities' Perceptions as Learners and Writers using Assitive Technology
Assistive technology, specifically, word prediction software holds great promise in supporting the writing process for students with learning disabilities. This thesis reports on a qualitative study that examined eight students’ self-perceptions as learners and writers using word prediction …
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Multi-Class Classification in Natural Language Processing
… Model . Empirical arguments are given using word-prediction and part of speech tagging tasks. Theoretical arguments present this thesis as an extension of the current classification methods which aim at disambiguating among many classes.
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An eye-movement analysis of the word-predictability effect
… was to identify the mechanism under-pinning the word-predictability effect, while a secondary aim was to investigate whether words are processed in serial or parallel. In five experiments, adults’ eye-movements were monitored as they read sentences for comprehension on a computer screen. In …
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Assistive Technology and the Impact of Occupations
… technology - AT (with a specific focus on word prediction, text to speech and speech recognition) from the perspectives of the end user, family and school personnel (e.g. teachers, therapists & specialists) across various contexts (e.g. home, school, community).</p> …
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Synthesizing controversial sentences for testing the brain-predictivity of language models
… developed for optimizing a similar objective (word prediction), their brain predictions are often correlated, even though the models differ along several architectural and conceptual features, yielding a major challenge for testing which model features are most relevant for predicting language …
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Cause, Composition, and Structure in Language
… computational motifs, namely the auto-regressive word prediction task, yields improvements in neural language model performance on targeted evaluations of models’ grammatical capabilities. I conclude by suggesting future directions in understanding the form and content of these causal generative …
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Perceptions of Working Memory Use in Communication by Users of Speech-Generating Devices
… in participants’ responses. Length of symbol/word sequences, word prediction, seeing the message as it is being created, attention to the conversational topic, and attempting to remember what their conversational partner said appeared to be judged as having the highest degree of importance for …
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Advancing System Models of Brain Processing via Integrative Benchmarking
… up to 70% ImageNet accuracy), and their next-word prediction performance in language. The better models predict internal neural activity, the better they match human behavioral outputs, with architecture substantially contributing to brain-like representations. Using the integrative …
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Exposing and correcting the gender bias in image captioning datasets and models
… image captioning model suffers. Also, due to the word-by-word prediction, the gender-activity bias in the data tends to influence the other words in the caption, resulting in the well know problem of label bias. In this work, we investigate gender bias in the COCO captioning dataset, and show that …
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Towards a phoneme-based predictive communication aid for nonspeaking individuals
… systems effectively to<br/>compose novel words and messages in spontaneous conversation. To address this problem, previous research has proposed the use of phoneme-based communication systems, which enable users to access a limited set of spoken phonemes (i.e. speech sounds). By combining …
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Towards automatic interpretation of A Fortiori arguments
… the best model achieves F1macro =.64±.005), and prediction of the hidden comparison property. The last task is automated in two ways, as a ranking task (where the best model achieves MAP=.34±.009) and as a masked word prediction task (where the best model achieves an accuracy of 66%). My results …
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On the induction of temporal structure by recurrent neural networks
… modelling via learning to predict the next word in a sentence. However, SRNs have also been shown to suffer from catastrophic forgetting, lack of syntactic systematicity and an inability to represent more than three levels of centre-embedding, due to the so-called 'vanishing gradients' …
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Using Principles from Cognitive Science to Analyze and Guide Language-Related Neural Networks
… First, human naming systems (e.g., a language’s words for colors such as “red” or “blue”) appear near-optimal in an informationtheoretic sense of compressing meaning into a small number of words; I ask how one might train AI systems that behave similarly. Second, people understand and produce …
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Towards Synergistic Understanding of Language Processing in Biological and Artificial Systems
… of training data, approximately 100 million words. Finally, to answer the third question, I draw inspiration from computational neuroscience to reveal how ANN language models learn a predictive model of linguistic input. By focusing on representational geometry, I demonstrate that ANN models …