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  2. Machine translation - Wikipedia

    en.wikipedia.org/wiki/Machine_translation

    A study by Stanford on improving this area of translation gives the examples that different probabilities will be assigned to "David is going for a walk" and "Ankit is going for a walk" for English as a target language due to the different number of occurrences for each name in the training data.

  3. Letter frequency - Wikipedia

    en.wikipedia.org/wiki/Letter_frequency

    The California Job Case was a compartmentalized box for printing in the 19th century, sizes corresponding to the commonality of letters. The frequency of letters in text has been studied for use in cryptanalysis, and frequency analysis in particular, dating back to the Arab mathematician al-Kindi (c. AD 801–873 ), who formally developed the method (the ciphers breakable by this technique go ...

  4. Text corpus - Wikipedia

    en.wikipedia.org/wiki/Text_corpus

    To exploit a parallel text, some kind of text alignment identifying equivalent text segments (phrases or sentences) is a prerequisite for analysis. Machine translation algorithms for translating between two languages are often trained using parallel fragments comprising a first-language corpus and a second-language corpus, which is an element ...

  5. Word list - Wikipedia

    en.wikipedia.org/wiki/Word_list

    A word list (or lexicon) is a list of a language's lexicon (generally sorted by frequency of occurrence either by levels or as a ranked list) within some given text corpus, serving the purpose of vocabulary acquisition.

  6. Bag-of-words model - Wikipedia

    en.wikipedia.org/wiki/Bag-of-words_model

    The bag-of-words model (BoW) is a model of text which uses an unordered collection (a "bag") of words. It is used in natural language processing and information retrieval (IR). It disregards word order (and thus most of syntax or grammar) but captures multiplicity .

  7. Statistical machine translation - Wikipedia

    en.wikipedia.org/.../Statistical_machine_translation

    Word-based translation systems can relatively simply be made to cope with high fertility, such that they could map a single word to multiple words, but not the other way about [citation needed]. For example, if we were translating from English to French, each word in English could produce any number of French words— sometimes none at all.

  8. Evaluation of machine translation - Wikipedia

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

    In the first example, where the text is translated into Italian then back into English—the English text is significantly garbled, but the Italian is a serviceable translation. In the second example, the text translated back into English is perfect, but the Portuguese translation is meaningless; the program thought "tit" was a reference to a ...

  9. Transfer-based machine translation - Wikipedia

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

    This representation can consist of a series of structures which represent the meaning. In these transfer systems predicates are typically produced. The translation also typically requires structural transfer. This level is used to translate between more distantly related languages (e.g. Spanish-English or Spanish-Basque, etc.)