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  2. BLEU - Wikipedia

    en.wikipedia.org/wiki/BLEU

    BLEU (bilingual evaluation understudy) is an algorithm for evaluating the quality of text which has been machine-translated from one natural language to another. Quality is considered to be the correspondence between a machine's output and that of a human: "the closer a machine translation is to a professional human translation, the better it is" – this is the central idea behind BLEU.

  3. Comparison of machine translation applications - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_machine...

    3.4.2: Yes: Rule-based, shallow transfer; all programs and language data are free and open source Babylon: Windows, Mac: Proprietary software: Depends on license ($9.90–$89 for one license) 10.3: No: Prompts to install the Babylon Toolbar, a browser hijacker which is difficult to remove. [2] [3] DeepL: Cross-platform (web application) SaaS

  4. Evaluation of machine translation - Wikipedia

    en.wikipedia.org/wiki/Evaluation_of_machine...

    A typical way for lay people to assess machine translation quality is to translate from a source language to a target language and back to the source language with the same engine. Though intuitively this may seem like a good method of evaluation, it has been shown that round-trip translation is a "poor predictor of quality". [1]

  5. 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 ...

  6. Neural machine translation - Wikipedia

    en.wikipedia.org/wiki/Neural_machine_translation

    Generative language models are not trained on the translation task, let alone on a parallel dataset. Instead, they are trained on a language modeling objective, such as predicting the next word in a sequence drawn from a large dataset of text. This dataset can contain documents in many languages, but is in practice dominated by English text. [36]

  7. ‘Connections’ Hints and Answers for NYT's Tricky ... - AOL

    www.aol.com/connections-hints-answers-nyts...

    PROGRAMMING LANGUAGES: BASIC, JAVA, PYTHON, RUBY 4. THINGS THAT CAN STRIKE: COBRA, INSPIRATION, LIGHTNING, UNION. How'd you do? Did You Miss a Few Days? Let's Catch You Up With Recent Connections ...

  8. Translator (computing) - Wikipedia

    en.wikipedia.org/wiki/Translator_(computing)

    Translator computing facilitates the conversion between these abstraction levels. [3] Overall, translator computing plays a crucial role in bridging the gap between software and hardware implementations, enabling developers to leverage the strengths of each platform and optimize performance, power efficiency, and other metrics according to the ...

  9. Translate Toolkit - Wikipedia

    en.wikipedia.org/wiki/Translate_Toolkit

    The Translate Toolkit is a localization and translation toolkit. It provides a set of tools for working with localization file formats and files that might need localization. The toolkit also provides an API on which to develop other localization tools.