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Chinese to Braille Translation Based on Braille word segmentation Using Statistical Model

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Journal of Shanghai Jiaotong university(Science) 2017年第1期22卷 82-86页

作者：王向东杨阳张金超姜文斌刘宏钱跃良 Beijing Key Laboratory of Mobile Computing and Pervasive Device Institute of Computing TechnologyChinese Academy of Sciences Institute of Computing Technology Chinese Academy of Sciences Jiangsu Enterprise Information Operation Center China Telecom Corporation Limited

Automatic translation of Chinese text to Chinese Braille is important for blind people in China to acquire information using computers or smart phones. In this paper, a novel scheme of Chinese-Braille translation is proposed. Under the scheme, a Braille word segmentation model based on statistical machine learning is trained on a Braille corpus, and Braille word segmentation is carried out using the statistical model directly without the stage of Chinese word segmentation. This method avoids establishing rules concerning syntactic and semantic information and uses statistical model to learn the rules stealthily and automatically. To further improve the performance, an algorithm of fusing the results of Chinese word segmentation and Braille word segmentation is also proposed. Our results show that the proposed method achieves accuracy of 92.81% for Braille word segmentation and considerably outperforms current approaches using the segmentation-merging scheme.

关键词： Chinese Braille word segmentation perceptron algorithm TP 391.1 A

Applying rough sets in word segmentation disambiguation based on maximum entropy model

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Journal of Harbin Institute of Technology(New Series) 2006年第1期13卷 94-98页

作者：姜维王晓龙关毅梁国华 School of Computer Science and Technology Harbin Institute of Technology Harbin 150001 China University of Technology Sydney Sydney

To solve the complicated feature extraction and long distance dependency problem in word segmentation Disambiguation （WSD）, this paper proposes to apply rough sets ill WSD based on the Maximum Entropy model. Firstly, rough set theory is applied to extract the complicated features and long distance features, even frnm noise or inconsistent corpus. Secondly, these features are added into the Maximum Entropy model, and consequently, the feature weights can be assigned according to the performance of the whole disambiguation mnltel. Finally, tile semantic lexicou is adopted to build class-hased rough set teatures to overcome data spareness. The experiment indicated that our method performed better than previous models, which got top rank in WSD in 863 Evaluation in 2003. This system ranked first and second respcetively in MSR and PKU open test in the Second International Chinese word segmentation Bankeoff held in 2005.

关键词： word segmentation feature extraction rough sets maximum entropy

The Research of the Maximum Length n-grams Priority Chinese word segmentation Method Based on Corpus Type Frequency Information

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The Research of the Maximum Length n-grams Priority Chinese ...

Pretrained Models and Evaluation Data for the Khmer Language

2012 National Conference on Information Technology and Computer Science

作者： Lu Pengyu School of Management Harbin Institute of Technology Harbin,China Jin Lijun School of Management Harbin Institute of Technology Harbin,China Jiang Bin School of Management Harbin Institute of Technology Harbin,China

In order to solve the difficulties to extract words in particular domain,we formulate a method of automatic word segmentation in Chinese based on corpus type frequency *** method can effectively extract n-gram words that are not predefined in a lexicon by setting the maximum length （n） of the n-gram word we want to extract from a sentence and the minimum threshold frequency the n-gram word appears in *** the real frequency the n-gram appears in corpus is above the threshold,the n-gram word will be *** there are two or more n-grams have the same length,the higher frequency one will be chosen,and then the next higher frequency one if any of its characters are not in previous one.

关键词： word segmentation word frequency n-gram word corpus type frequency information

来源： cnki会议评论

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cnki会议

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Tsinghua Science and Technology 2022年第4期27卷 709-718页

作者： Shengyi Jiang Sihui Fu Nankai Lin Yingwen Fu School of Information Science and Technology Guangdong University of Foreign StudiesGuangzhou 510000China Guangzhou Key Laboratory of Multilingual Intelligent Processing Guangdong University of Foreign StudiesGuangzhou 510000China

Trained on a large corpus,pretrained models(PTMs)can capture different levels of concepts in context and hence generate universal language representations,which greatly benefit downstream natural language processing(NLP)*** recent years,PTMs have been widely used in most NLP applications,especially for high-resource languages,such as English and ***,scarce resources have discouraged the progress of PTMs for low-resource ***-based PTMs for the Khmer language are presented in this work for the first *** evaluate our models on two downstream tasks:Part-of-speech tagging and news *** dataset for the latter task is *** demonstrate the effectiveness of the Khmer *** addition,we find that the current Khmer word segmentation technology does not aid performance *** aim to release our models and datasets to the community in hopes of facilitating the future development of Khmer NLP applications.

关键词： pretrained models Khmer language word segmentation part-of-speech(POS)tagging news categorization

Improving the Syllable-Synchronous Network SearchAlgorithm for word Decoding in ContinuousChinese Speech Recognition

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Journal of Computer Science & Technology 2000年第5期15卷 461-471页

作者：郑方武健宋战江 CenterofSpeechTechnology StateKeyLabofIntelligentTechnologyandSystemsDepartmentofComputerScienceandTechnologyTsinghuaUniversityBeijing100084P.R.China

The previously proposed syllable-synchronous network search (SSNS) algorithm plays a very important role in the word decoding of the continuous Chinese speech recognition and achieves satisfying performance. Several related key factors that may affect the overall word decoding effect are carefully studied in this paper, including the perfecting of the vocabulary, the big-discount Turing re-estimating of the N-Gram probabilities, and the managing of the searching path buffers. Based on these discussions, corresponding approaches to improving the SSNS algorithm are proposed. Compared with the previous version of SSNS algorithm, the new version decreases the Chinese character error rate (CCER) in the word decoding by 42.1% across a database consisting of a large number of testing sentences (syllable strings).

关键词： large-vocabulary continuous Chinese speech recognition word decoding syllable- synchronous network search word segmentation

A novel unsupervised method for new word extraction

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Science China(Information Sciences) 2016年第9期59卷 11-21页

作者： Lili MEI Heyan HUANG Xiaochi WEI Xianling MAO Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Department of Computer Science and TechnologyBeijing Institute of Technology

New words could benefit many NLP tasks such as sentence chunking and sentiment analysis. However, automatic new word extraction is a challenging task because new words usually have no fixed language pattern, and even appear with the new meanings of existing words. To tackle these problems, this paper proposes a novel method to extract new words. It not only considers domain specificity, but also combines with multiple statistical language knowledge. First, we perform a filtering algorithm to obtain a candidate list of new words. Then, we employ the statistical language knowledge to extract the top ranked new words. Experimental results show that our proposed method is able to extract a large number of new words both in Chinese and English corpus, and notably outperforms the state-of-the-art methods. Moreover, we also demonstrate our method increases the accuracy of Chinese word segmentation by 10% on corpus containing new words.

关键词： new word extraction word segmentation domain specificity statistical language knowledge domain word extraction

Chinese word Boundary Ambiguity and Unknown word Resolution Using Unsupervised Methods

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同方期刊数据库

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High Technology Letters 2000年第2期6卷 29-39页

作者：傅国宏 Harbin Inst of Technology Harbin China

An unsupervised framework to partially resolve the four issues, namely ambiguity, unknown word, knowledge acquisition and efficient algorithm, in developing a robust Chinese segmentation system is described. It first proposes a statistical segmentation model integrating the simplified character juncture model (SCJM) with word formation power. The advantage of this model is that it can employ the affinity of characters inside or outside a word and word formation power simultaneously to process disambiguation and all the parameters can be estimated in an unsupervised way. After investigating the differences between real and theoretical size of segmentation space, we apply A * algorithm to perform segmentation without exhaustively searching all the potential segmentations. Finally, an unsupervised version of Chinese word formation patterns to detect unknown words is presented. Experiments show that the proposed methods are efficient.

关键词： word segmentation Character Juncture Work formation pattern

Song Ci Style Automatic Identification

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Journal of Donghua University(English Edition) 2010年第2期27卷 181-184页

作者：郑旭玲周昌乐曾华琳 Department of Cognitive Science Fujian Key Laboratory of the Brain-like Intelligent SystemsXiamen University

To identify Song Ci style automatically,we put forward a novel stylistic text categorization approach based on words and their semantic in this paper. And a modified special word segmentation method,a new semantic relativity computing method based on HowNet along with the corresponding word sense disambiguation method are proposed to extract words and semantic features from Song Ci. Experiments are carried out and the results show that these methods are effective.

关键词： stylistic text categorization word sense disambiguation (WSD) word segmentation HowNet Song Ci

Design and Realization of Nature Language Processing in The Application of Computer-assisted Teaching

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Design and Realization of Nature Language Processing in The ...