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Conference Papers Year : 2010

Similar N-Gram Language Model


This paper describes an extension of the n-gram language model: the similar n-gram language model. The estimation of the probability P(s) of a string s by the classical model of order n is computed using statistics of occurrences of the last n words of the string in the corpus, whereas the proposed model further uses all the strings s' for which the Levenshtein distance to s is smaller than a given threshold. The similarity between s and each string s' is estimated using co-occurrence statistics. The new P(s) is approximated by smoothing all the similar n-gram probabilities with a regression technique. A slight but statistically significant decrease in the word error rate is obtained on a state-of-the-art automatic speech recognition system when the similar n-gram language model is interpolated linearly with the n-gram model.
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inria-00540428 , version 1 (26-11-2010)


  • HAL Id : inria-00540428 , version 1


Christian Gillot, Christophe Cerisara, David Langlois, Jean-Paul Haton. Similar N-Gram Language Model. INTERSPEECH 2010, Sep 2010, Tokyo, Japan. pp.1824-1827. ⟨inria-00540428⟩
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