The Use of Clustering Techniques for Language Modeling - Application to Asian Languages

by Jianfeng Gao , Joshua T. Goodman , Jiangbo Miao

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Datum	Value	Source
TITLE	The Use of Clustering Techniques for Language Modeling - Application to Asian Languages	user correction - Legacy Corrections
AUTHOR NAME	Jianfeng Gao	SVM HeaderParse 0.1
AUTHOR AFFIL	Microsoft Research	SVM HeaderParse 0.2
AUTHOR ADDR	China; Beijing, 100080, P.R.C	SVM HeaderParse 0.1
AUTHOR NAME	Joshua T. Goodman	SVM HeaderParse 0.1
AUTHOR AFFIL	; Microsoft Research, Redmond; 1	SVM HeaderParse 0.2
AUTHOR ADDR	; Washington 98052, USA	SVM HeaderParse 0.1
AUTHOR NAME	Jiangbo Miao	SVM HeaderParse 0.1
AUTHOR AFFIL	Department of Computer &; Information Sciences	SVM HeaderParse 0.2
AUTHOR ADDR	University of Delaware, USA	SVM HeaderParse 0.1
ABSTRACT	Cluster-based n-gram modeling is a variant of normal word-based n-gram modeling. It attempts to make use of the similarities between words. In this paper, we present an empirical study of clustering techniques for Asian language modeling. Clustering is used to improve the performance (i.e. perplexity) of language models as well as to compress language models. Experimental tests are presented for cluster-based trigram models on a Japanese newspaper corpus, and on a Chinese heterogeneous corpus.	user correction - Legacy Corrections
CITATIONS	40 found	ParsCit 1.0