Open Access Open Access  Restricted Access Subscription or Fee Access

Improved Application of K-N Smooth Linear Interpolation Method in Measurement of English Readability Based on Statistical Language Model

Jie Wu


This paper first reviews previous researches on English Readability and puts forward the necessities of studying English readability on the basis of Statistical Language Model. Then, it analyzes how to construct measurement of English Readability based on Statistical Language Model and proposes that sparse data is a problem that the study must confront. To solve this problem, this paper makes some improvements to the Kneser-Ney?K-N?smooth linear interpolation method, tests the effectiveness of the improved K-N smooth linear interpolation method with data from spoken and written English corpus, and solves the problem of sparse data in constructing measurement of English Readability, based on Statistical Language Model.


Statistical Language Model, Kneser-Ney, corpus, sparse data.

Full Text:


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.