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Reseach Article

Adaptive Hybrid POS Cache based Semantic Language Model

by Manzoor Ahmad Chachoo, S. M. K. Quadri
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 39 - Number 13
Year of Publication: 2012
Authors: Manzoor Ahmad Chachoo, S. M. K. Quadri
10.5120/4878-7310

Manzoor Ahmad Chachoo, S. M. K. Quadri . Adaptive Hybrid POS Cache based Semantic Language Model. International Journal of Computer Applications. 39, 13 ( February 2012), 7-10. DOI=10.5120/4878-7310

@article{ 10.5120/4878-7310,
author = { Manzoor Ahmad Chachoo, S. M. K. Quadri },
title = { Adaptive Hybrid POS Cache based Semantic Language Model },
journal = { International Journal of Computer Applications },
issue_date = { February 2012 },
volume = { 39 },
number = { 13 },
month = { February },
year = { 2012 },
issn = { 0975-8887 },
pages = { 7-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume39/number13/4878-7310/ },
doi = { 10.5120/4878-7310 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:26:20.774419+05:30
%A Manzoor Ahmad Chachoo
%A S. M. K. Quadri
%T Adaptive Hybrid POS Cache based Semantic Language Model
%J International Journal of Computer Applications
%@ 0975-8887
%V 39
%N 13
%P 7-10
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a language model as an improvement over the stochastic language model for developing a syntactic structure based on word dependencies in local and non local domain. The model copes with the issues of limited amount of training material and the exploitation of the linguistic constraints of the language. The proposed model is a dynamic probabilistic model which uses word dependencies based on their part of speech tags along with the tri-gram Model but also takes care of the influence of the word which are very far from the word being considered in a text and stores the word history in a dynamic cache for information mining using long distance dependency. The model based on second order Hidden Markov Model has been used and an improvement of 2% has been observed in the word error rate and 4% reduction in the perplexity when compared to the normal tri-gram model.

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Index Terms

Computer Science
Information Sciences

Keywords

Language Model Dynamic language model Part of Speech POS Language Model Word Dependencies Speech recognition system