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  2. Example-based machine translation - Wikipedia

    en.wikipedia.org/wiki/Example-based_machine...

    Example-based machine translation (EBMT) is a method of machine translation often characterized by its use of a bilingual corpus with parallel texts as its main knowledge base at run-time. It is essentially a translation by analogy and can be viewed as an implementation of a case-based reasoning approach to machine learning .

  3. Comparison of different machine translation approaches

    en.wikipedia.org/wiki/Comparison_of_different...

    A DMT system is designed for a specific source and target language pair and the translation unit of which is usually a word. Translation is then performed on representations of the source sentence structure and meaning respectively through syntactic and semantic transfer approaches. A transfer-based machine translation system involves three ...

  4. Image translation - Wikipedia

    en.wikipedia.org/wiki/Image_translation

    Image translation is the machine translation of images of printed text (posters, banners, menus, screenshots etc.). This is done by applying optical character recognition (OCR) technology to an image to extract any text contained in the image, and then have this text translated into a language of their choice, and the applying digital image processing on the original image to get the ...

  5. Interlingual machine translation - Wikipedia

    en.wikipedia.org/wiki/Interlingual_machine...

    For example, it might be trained just for Japanese-English and Korean-English translation, but can perform Japanese-Korean translation. The system appears to have learned to produce a language-independent intermediate representation of language (an "interlingua"), which allows it to perform zero-shot translation by converting from and to the ...

  6. Neural machine translation - Wikipedia

    en.wikipedia.org/wiki/Neural_machine_translation

    Or one can include one or several example translations in the prompt before asking to translate the text in question. This is then called one-shot or few-shot learning, respectively. For example, the following prompts were used by Hendy et al. (2023) for zero-shot and one-shot translation: [35]

  7. Semantic parsing - Wikipedia

    en.wikipedia.org/wiki/Semantic_parsing

    Machine Translation: To improve the quality and context of translation, machine translation entails comprehending the semantics of one language in order to translate it into another accurately. Text Analytics: Business intelligence and social media monitoring benefit from the meaningful insights that can be extracted from text data through ...

  8. Transfer-based machine translation - Wikipedia

    en.wikipedia.org/wiki/Transfer-based_machine...

    This is basically dictionary translation; the source language lemma (perhaps with sense information) is looked up in a bilingual dictionary and the translation is chosen. Structural transfer. While the previous stages deal with words, this stage deals with larger constituents, for example phrases and chunks. Typical features of this stage ...

  9. Transcreation - Wikipedia

    en.wikipedia.org/wiki/Transcreation

    Transcreation is a term coined from the words "translation" and "creation", and a concept used in the field of translation studies to describe the process of adapting a message from one language to another, while maintaining its intent, style, tone, and context.