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dc.contributor.authorPakpoom, Mookdarsanit-
dc.contributor.authorLawankorn, Mookdarsanit-
dc.date.accessioned2024-03-22T18:38:15Z-
dc.date.available2024-03-22T18:38:15Z-
dc.date.issued2023-12-01-
dc.identifier.issn2616-6127 2617-4383-
dc.identifier.urihttp://dspace.azjhpc.org/xmlui/handle/123456789/266-
dc.description.abstractText-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.en_US
dc.publisherAzerbaijan Journal of High Performance Computingen_US
dc.subjectText-to-Image Translationen_US
dc.subjectImage Generationen_US
dc.subjectThai Prompt Engineeringen_US
dc.subjectStable Diffusion Modelen_US
dc.titleThai Text-to-Image Prompt Engineering by Pre-trained Large Language with Stable Diffusion Modelen_US
dc.typeArticleen_US
dc.source.journaltitleAzerbaijan Journal of High Performance Computingen_US
dc.source.volume6en_US
dc.source.issue1en_US
dc.source.beginpage171en_US
dc.source.endpage190en_US
dc.source.numberofpages20en_US
Appears in Collections:Azerbaijan Journal of High Performance Computing

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