N-gram smoothing based on modeling of expectation of n-gram occurrence
Keywords:
language model, smoothing techniquesAbstract
It is shown that expectation of n-gram frequency of occurrence depends on the size of the training set and the size of the dictionary, which has been formed on the basis of this set. A method for smoothing of n-gram language model regarding probabilities of n-grams of lower order is proposed. This approach is based on the modeling of expectation function of n-gram occurrence probability. We suggest enlarging the size of the training set on the expected number of unseen n-grams instead of discounting maximum n-gram probability. To model the number of unseen n-grams expectation function of n-gram frequency of occurrence is extrapolated to zero frequency. Expectation function is modeled by the statistical analysis of occurrences of words in texts.References
Published
2011-12-01
How to Cite
Zykov, A. (2011). N-gram smoothing based on modeling of expectation of n-gram occurrence. SPIIRAS Proceedings, 4(19), 146-158. https://doi.org/10.15622/sp.19.8
Section
Articles
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