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  2. Wordtune - Wikipedia

    en.wikipedia.org/wiki/Wordtune

    Wordtune is an AI powered reading and writing companion capable of fixing grammatical errors, understanding context and meaning, suggesting paraphrases or alternative writing tones, and generating written text based on context. [1] [2] [3] It is developed by the Israeli AI company AI21 Labs. [4] [5] [6] [7]

  3. QuillBot - Wikipedia

    en.wikipedia.org/wiki/QuillBot

    Download QR code; Print/export ... uses artificial intelligence to rewrite and paraphrase text. [1] [2 ... QuillBot has a user base that includes both free and ...

  4. Paraphrasing (computational linguistics) - Wikipedia

    en.wikipedia.org/wiki/Paraphrasing...

    Paraphrase or paraphrasing in computational linguistics is the natural language processing task of detecting and generating paraphrases. Applications of paraphrasing are varied including information retrieval, question answering , text summarization , and plagiarism detection . [ 1 ]

  5. Paraphrase - Wikipedia

    en.wikipedia.org/wiki/Paraphrase

    A paraphrase or rephrase (/ ˈ p ær ə ˌ f r eɪ z /) is the rendering of the same text in different words without losing the meaning of the text itself. [1] More often than not, a paraphrased text can convey its meaning better than the original words. In other words, it is a copy of the text in meaning, but which is different from the original.

  6. Literal translation - Wikipedia

    en.wikipedia.org/wiki/Literal_translation

    Literal translation, direct translation, or word-for-word translation is the translation of a text done by translating each word separately without analysing how the words are used together in a phrase or sentence. [1] In translation theory, another term for literal translation is metaphrase (as opposed to paraphrase for an analogous translation).

  7. Automatic summarization - Wikipedia

    en.wikipedia.org/wiki/Automatic_summarization

    Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.

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