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Technology for Translating, Visualizing, and Generating Recipes

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This book details the process of building a Chinese-English machine translation system that automatically translates Chinese recipes into English through machine processing without human intervention ( TransRecipe ). This system is able to translate recipes into pictures and videos ( VisualRecipe )...

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Autor principal: Sin-wai, Chan
Formato: Online
Idioma:inglês
Publicado em: Taylor & Francis 2026
Assuntos:
Computational linguistics
Deep learning applications
Food informatics
Image-based data processing
Natural language processing
Culinary data analysis
Automated recipe generation from video
System testing
Machine translation
Translation methods
Database creation
Computer-aided design
System debugging
Translating numerals
Corpus
Visual translation
Techno-humanities
thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics
thema EDItEUR::C Language and Linguistics::CF Linguistics
thema EDItEUR::C Language and Linguistics::CF Linguistics::CFP Translation and interpretation
Acesso em linha:https://library.oapen.org/handle/20.500.12657/110441
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Resumo:This book details the process of building a Chinese-English machine translation system that automatically translates Chinese recipes into English through machine processing without human intervention ( TransRecipe ). This system is able to translate recipes into pictures and videos ( VisualRecipe ) through image technology and develop a system that generates a recipe from a video on dish preparation ( GenRecipe ) through deep learning. Recipe processing is covered in four parts across ten chapters. The first part, Translating Recipes , studies the machine processing of different parts of recipes for the construction of the TransRecipe system. The second part, Visualizing Recipes , is about the creation of the VisualRecipe system through image technology and a demonstration of its operations in practice. The third part, Generating Recipes , is about recipe creation through deep learning and the creation of the GenRecipe system. Lastly, the book concludes by looking into the future of recipe technology. The title is a vital read for researchers and students in translation technology, multimodal translation, and techno-humanities.

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