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Introduction to the special issue on statistical language modeling
Jianfeng Gao, Chin-Yew Lin
Lexical triggers and latent semantic analysis for cross-lingual language model adaptation
Woosung Kim, Sanjeev Khudanpur
In-domain texts for estimating statistical language models are not easily found for most languages of the world. We present two techniques to take advantage of in-domain text resources in other languages. First, we extend the notion of...
A hybrid language model based on a combination of N-grams and stochastic context-free grammars
Diego Linares, José-Miguel Benedí, Joan-Andreu Sánchez
In this paper, a hybrid language model is defined as a combination of a word-based <i>n</i>-gram, which is used to capture the local relations between words, and a category-based stochastic context-free grammar (SCFG) with a word...
A discriminative HMM/N-gram-based retrieval approach for mandarin spoken documents
Berlin Chen, Hsin-Min Wang, Lin-Shan Lee
In recent years, statistical modeling approaches have steadily gained in popularity in the field of information retrieval. This article presents an HMM/N-gram-based retrieval approach for Mandarin spoken documents. The underlying characteristics...
Example-based sentence reduction using the hidden markov model
Minh Le Nguyen, Susumu Horiguchi, Akira Shimazu, Bao Tu Ho
Sentence reduction is the removal of redundant words or phrases from an input sentence by creating a new sentence in which the gist of the original meaning of the sentence remains unchanged. All previous methods required a syntax parser before...
A maximum-entropy chinese parser augmented by transformation-based learning
Pascale Fung, Grace Ngai, Yongsheng Yang, Benfeng Chen
Parsing, the task of identifying syntactic components, e.g., noun and verb phrases, in a sentence, is one of the fundamental tasks in natural language processing. Many natural language applications such as spoken-language understanding, machine...