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 20 of 34 for “"model adaptation"”.
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MODEL ADAPTATION FOR EDGE AI
… due to their computational demands. Existing model compression techniques often fall short by being oblivious to downstream user-specific tasks. This thesis addresses the challenge of adapting DNN models effectively on resource-limited hardware, advocating for flexible and efficient models. …
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Speaker model adaptation in automatic speech recognition.
… multiple template representation and speaker adaptation. This thesis describes a study of employing different speaker adaptation techniques in an attempt to improve the performance of a continuous density HMM-based speaker independent speech recogniser. Two alternative approaches which …
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Toward automatic model adaptation for structured domains
… learning effort to succeed, an appropriate model must be chosen. This is a difficult task in which one must balance flexibility, so that the model can capture the complexities of the domain, and simplicity, so that the model does not overfit to irrelevant characteristics of the training …
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Acoustic model adaptation for recognition of dysarthric speech
Item reinstated by Sarah Shreeves (sshreeve@illinois.edu) on 2014-06-28T10:00:22Z Item was in collections: Dissertations and Theses - Electrical and Computer Engineering (ID: 446) Graduate Theses and Dissertations at Illinois (ID: 204) No. of bitstreams: 2 Sharma_Harsh.pdf: 1379121 bytes, checksum: …
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Acoustic Model Adaptation For Reverberation Robust Automatic Speech Recognition
… to speech recognition, we propose "Semi-blind adaptation" technique which adapts the clean acoustic models to the reverberant environment and thus provide improved performance. Semi-blind adaptation technique works in two phases, in the first phase reverberation model is estimated and in the …
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The Geriatric Cancer Experience in End of Life: Model Adaptation and Testing
… Health recommends the development of conceptual models to increase rigor and improve evaluation in research. Validated models are essential to guide conceptualizations of phenomena, selection of variables and development of testable hypotheses. Structural equation modeling (SEM) is a methodology …
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Spot the Odd Song Out: Similarity Model Adaptation and Analysis using Relative Human Ratings
… recommendation and exploration utilise various models for similarity prediction to satisfy users’ expectations. Perceived similarity is specific to the individual and influenced by a number of factors such as cultural background and age. Thus, adapting a generic model to human similarity data is …
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Improving Controllability in Diffusion-Based Image Inpainting through Structured Workflows and Preference-Based Model Adaptation
… is developed that fine-tunes a diffusion model for controlled object generation and integrates it into an agentic pipeline for context-aware scene inpainting. Building on this, the second approach addresses the limitation that workflow-level control alone does not ensure that the …
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Vision and Learning for Intelligent Human -Computer Interaction
… motion analysis tasks: non-stationary color model adaptation for efficient localization, multiple visual cues integration for robust tracking, and learning motion models for capturing articulated hand motion. Besides, this dissertation describes a novel statistical learning method, the …
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Change detection for activity recognition.
… of users. The accuracy of the generated model often reduces during classification of new instances due to the non-stationary sensor data and variations in user characteristics. Thus, there is a need to adapt the classification model to new user haracteristics. However, the existing …
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Automatic Speech Recognition Quality Estimation
… hypotheses scenario. In the former, a regression model is used to predict the WER score of each single hypothesis that is created through a single automatic transcription channel. In the latter, a ranking model is used to predict the order of multiple hypotheses with respect to their quality. …
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Development of Adaptive and Factorized Neural Models for MPC of Industrial Systems
… require further investigations. Adaptive modelling techniques using radial basis function (RBF) networks often provide competitive modelling performances but encounter slow recovery speed when processes operating regions are shifted largely. In addition, RBF networks based model predictive …
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Language Modeling for limited-data domains
… performance often relies on approaches involving model adaptation and combination. In such domains, language models are often constructed by interpolating component models trained from partially matched corpora. Instead of simple linear interpolation, we introduce a generalized linear …
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Multi-modal and deep learning for robust speech recognition
… present. In this thesis, speech denoising and model adaptation for robust speech recognition were studied, and four novel methods were introduced to improve ASR robustness. First, we developed an ASR system using multi-channel information from microphone arrays via accurate speaker tracking …
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Efficient Knowledge Transfer and Adaptation for Speech and Beyond
… the field of efficient knowledge transfer and adaptation in the realm of speech processing. It is structured to address the limitations of transfer learning in dynamically evolving audio and speech processing contexts, particularly through novel approaches for class-incremental learning, …
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Computational user intent modeling
User modeling is essential for any information service system (e.g., search engines, recommender systems, and computational advertising) to optimize its service to the end users. The level of user understanding directly determines the upper bound of optimality that such a system can achieve when …
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Examining the role of business analytics for the adaptation of business models among South Africa SMEs
… of business analytics (BA) in adapting business models among SMEs. Design/methodology/approach: A qualitative multiple-case method was employed through semi-structured interviews of SME business owners and managers Findings: The examination conducted in the study through thematic analysis …
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Machine Learning Methods for Wastewater Treatment Plants
… and develops a multiclass classification model and suitable post-processing and automation strategies. Among the tested models, the best-performing were tree-based algorithms, particularly gradient boosting methods such as LightGBM. This model was implemented in real plants as a Decision …
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The evolution of annuality in association with a shift to more arid environments in the daisy genera Ifloga and Tricogyne
An annual life history is often viewed as a model adaptation to arid environments. Annuality is predicted to have evolved in response to low adult survival and high seedling survival. In this study I evaluated the idea that increases in aridity should be associated with the evolution of an annual …
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A framework for evaluating semi-structured hierarchical data using language models
Recent advances in large language models have intensified interest in applying them to tasks such as extractive question answering over semi-structured hierarchical data represented in markup languages. The conventional practice of linearising markup to plain text involves removing structural …
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