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  2. Natural language generation - Wikipedia

    en.wikipedia.org/wiki/Natural_language_generation

    Natural language generation (NLG) is a software process that produces natural language output. A widely-cited survey of NLG methods describes NLG as "the subfield of artificial intelligence and computational linguistics that is concerned with the construction of computer systems that can produce understandable texts in English or other human languages from some underlying non-linguistic ...

  3. Automatic Complaint-Letter Generator - Wikipedia

    en.wikipedia.org/wiki/Automatic_Complaint-Letter...

    In 1995, the generator had "282 sentence skeletons, 170 independent clauses, 183 adjectives, and 123 nouns". The combination of these elements can form more than one billion sentences. [ 7 ] As of September 2009, the generator has expanded to 3379 independent clauses, 618 adjectives, and 497 nouns. [ 8 ]

  4. Speech synthesis - Wikipedia

    en.wikipedia.org/wiki/Speech_synthesis

    Work to personalize a synthetic voice to better match a person's personality or historical voice is becoming available. [94] A noted application, of speech synthesis, was the Kurzweil Reading Machine for the Blind which incorporated text-to-phonetics software based on work from Haskins Laboratories and a black-box synthesizer built by Votrax .

  5. Rule-based machine translation - Wikipedia

    en.wikipedia.org/wiki/Rule-based_machine_translation

    Minimally, to get a German translation of this English sentence one needs: A dictionary that will map each English word to an appropriate German word. Rules representing regular English sentence structure. Rules representing regular German sentence structure. And finally, we need rules according to which one can relate these two structures ...

  6. Postmodernism Generator - Wikipedia

    en.wikipedia.org/wiki/Postmodernism_Generator

    The Postmodernism Generator is a computer program that automatically produces "close imitations" of postmodernist writing. It was written in 1996 by Andrew C. Bulhak of Monash University using the Dada Engine, a system for generating random text from recursive grammars . [ 1 ]

  7. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    According to the authors' note, [3] CBOW is faster while skip-gram does a better job for infrequent words. After the model is trained, the learned word embeddings are positioned in the vector space such that words that share common contexts in the corpus — that is, words that are semantically and syntactically similar — are located close to ...

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