Browsing by Author "Laszlo, Bogdan"

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    Creating Synthetic Dialogue Datasets for NLU Training. An Approach Using Large Language Models
    (2024-06-20) Laszlo, Bogdan; University of Gothenburg / Department of Philosophy,Lingustics and Theory of Science; Göteborgs universitet / Institutionen för filosofi, lingvistik och vetenskapsteori
    This thesis explores the topic of using the GPT-4 large language model, to generate high-quality, diverse synthetic dialogue datasets for training Natural Language Understanding (NLU) models in task-oriented dialogue systems. By employing a schema-guided framework and prompt engineering, the study explores whether synthetic data can replace real-world data. The research focuses on domain classification, active intent classification, and slot multi-labelling. Results show that while synthetic datasets can moderately match real-world data, issues like quality and annotation inconsistency persist.