Please use this identifier to cite or link to this item:
Title: On the use of morphological constraints in N-gram statistical language model
Authors: Ghaoui, A.
Yvon, François
Mokbel, Chafic 
Chollet, Gérard
Affiliations: Department of Electrical Engineering 
Issue Date: 2005
Part of: INTERSPEECH 2005
Conference: European Conference on Speech Communication and Technology (9th : 4-8 Sep 2005 : Lisbon, Portugal) 
State of the art Speech Recognition systems use statistical language modeling and in particular N-gram models to represent the language structure. The Arabic language has a rich morphology, which motivates the introduction of morphological constraints in the language model. Class-based N-gram models have shown satisfactory results, especially for language model adaptation and training from reduced datasets. They were also proven quite effective in their use of memory space. In this paper, we investigate a new morphological class-based language model. Morphological rules are used to derive the different words in a class from their stem. As morphological analyzer, a rule-based stemming method is proposed for the Arabic language. The language model has been evaluated on a database composed of articles from Lebanese newspaper Al-Nahar for the years 1998 and 1999. In addition, a linear interpolation between the N-gram model and the morphological model is also evaluated. Preliminary experiments detailed in this paper show satisfactory results.
Type: Conference Paper
Appears in Collections:Department of Electrical Engineering

Show full item record

Record view(s)

checked on Oct 23, 2021

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.