Please use this identifier to cite or link to this item: http://dspace.azjhpc.org/xmlui/handle/123456789/266
Title: Thai Text-to-Image Prompt Engineering by Pre-trained Large Language with Stable Diffusion Model
Authors: Pakpoom, Mookdarsanit
Lawankorn, Mookdarsanit
Keywords: Text-to-Image Translation;Image Generation;Thai Prompt Engineering;Stable Diffusion Model
Issue Date: 1-Dec-2023
Publisher: Azerbaijan Journal of High Performance Computing
Abstract: Text-to-image (T2I) generation is a new area of large language models (LLMs), a type of prompt engineering involving inputting a textual description to generate an image. To shift a new paradigm of Thai natural language processing (Thai-NLP), this paper first presents state-of-the-art Thai Text-to-Image prompt engineering (TH-T2I) to translate Thai text into a semantic image according to the semantic Thai textual description. The pre-trained SCB-MT-EN-TH model is employed for Text-to-Text (T2T) translation. Moreover, the image generation is done according to a semantic text prompt by a stable diffusion model. The T2T is evaluated by Bi-lingual Evaluation Understudy (BLEU), while T2I is done by Inception and Frechet Inception Distance (FID). The images generated by TH-T2I were of high quality, as measured by Inception and FID. TH-T2I contributes to a T2I baseline model in Thai, preserving the Thai cultural language on digital heritage.
URI: http://dspace.azjhpc.org/xmlui/handle/123456789/266
ISSN: 2616-6127 2617-4383
Journal Title: Azerbaijan Journal of High Performance Computing
Volume: 6
Issue: 1
First page number: 171
Last page number: 190
Number of pages: 20
Appears in Collections:Azerbaijan Journal of High Performance Computing

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