Automatic language identification using both N-gram and word inf

Data processing: speech signal processing – linguistics – language – Linguistics – Natural language

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704 10, G06F 1727

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active

061673692

ABSTRACT:
The predominant language of a sample text is automatically identified using probability data that include N-gram probability data for at least one language and word probability data for at least one language. The N-gram probability data of a language indicate, for each N-gram, the probability that it occurs if the language is predominant. Similarly, the word probability data of a language indicate, for each word, the probability that it occurs if the language is predominant. The probability data are used to automatically obtain sample probability data for at least two languages. The sample probability data include N-gram probability information for at least one language and word probability information for at least one language. The sample probability data are used to automatically obtain language identifying data identifying the language whose sample probability data indicate the highest probability. The N-grams can be trigrams, while the words can be short words of no more than five characters. Some languages can have both trigram and word probabilities, while some can have only trigram probabilities.

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