N-gram Distribution Based Language Model Adaptation

机译：基于N元语法分布的语言模型适应

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This paper presents two techiques for language model (LM) adaptation. The first aims to build a more general LM. We propose a distribution-based pruning of n-gram LMs, where we prune n-grams that are likely to be infrequent in a new document. Experimental results show that the distribution-based pruning mehtod performed up to 9

机译：本文介绍了两种语言模型（LM）自适应技术。第一个目标是建立一个更通用的LM。我们建议对n-gram LM进行基于分布的修剪，在其中修剪新文档中可能很少出现的n-gram。实验结果表明，基于分布的修剪方法最多可以执行9次

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《6th International Conference on Spoken Language Processing ICSLP 2000 Oct.16-Oct.20 2000 Beijing International Convention Center, Beijing, China》|2000年|p.497-500|共4页
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Jianfeng; Gao; Mingjing Li; Kai-Fu Lee;
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中图分类自动化技术、计算机技术;
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2. Language Model Adaptation for Fixed Phrases by Amplifying Partial N-gram Sequences [J] . Tomoyosi Akiba, Katunobu Itou, Atsushi Fuji Systems and Computers in Japan . 2007,第4期

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3. Converting Continuous-Space Language Models into N-gram Language Models with Efficient Bilingual Pruning for Statistical Machine Translation [J] . RUI WANG, MASAO UTIYAMA, ISAO GOTO, ACM transactions on Asian language information processing . 2016,第3期

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4. N-gram Distribution Based Language Model Adaptation [C] . Jianfeng, Gao, Mingjing Li, International conference on spoken language processing . 2000

机译：基于N-GRAM分布的语言模型适应
5. Language-independent text learning with statistical n-gram language models. [D] . Peng, Fuchun. 2003

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6. Modeling Actions of PubMed Users with N-Gram Language Models [O] . Jimmy Lin, W. John Wilbur -1

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7. TASK ADAPTATION USING MAP ESTIMATION IN N-GRAM LANGUAGE MODELING [O] . Hirokazu Masatakiy, Yoshinori Sagisakay, Kazuya Hisakiz, 2009

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8. Investigation of Back-off Based Interpolation Between Recurrent Neural Network and N-gram Language Models (Author's Manuscript). [R] . Chen, X., Liu, X., Gales, M. J. F., 2016

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N-gram Distribution Based Language Model Adaptation

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