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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 Hits 41 – 60 of 74 41 Unsupervised Extraction of Recurring Words from Infant-Directed Speech Fergus R. Mcinnes; Sharon J. Goldwater In: http://www.cstr.inf.ed.ac.uk/downloads/publications/2011/mcinnes_cogsci2011.pdf BASE Show details 42 Unsupervised Extraction of Recurring Words from Infant-Directed Speech Fergus R. Mcinnes; Sharon J. Goldwater In: http://homepages.inf.ed.ac.uk/sgwater/papers/cogsci11_wordextract.pdf BASE Show details 43 Generality for Multi-language of Word Segmentation Method Using Inductive Learning Zhongjian Wang; Kenji Araki; Koji Tochinai In: http://www.afnlp.org/archives/pacling2001/pdf/wang-z.pdf BASE Show details 44 Which is More Suitable for Chinese Word Segmentation, the Generative Model or the Discriminative One? F∗ Kun Wang; Chengqing Zong; Keh-yih Su In: http://www.nlpr.ia.ac.cn/cip/zongpublications/2009/2009 paclic23-827-834-wang kun.pdf BASE Show details 45 RESEARCH ARTICLE OPEN ACCESS Extract the Punjabi Word from Machine Printed Document Images Gaurav Singla; Dr. Parmod Kumar In: http://www.ijera.com/papers/Vol3_issue5/BJ35343348.pdf BASE Show details 46 Segmentation of Printed Text in Devanagari Script and Gurmukhi Script Vijay Kumar ECD, Deptt. Iit Roorkee; Pankaj K. Sengar In: http://www.ijcaonline.org/volume3/number8/pxc3871058.pdf BASE Show details 47 A Word-Finding Automaton for Chinese Sentence Tokenization Hong-I Ng; Kim-teng Lua In: http://cslp.comp.nus.edu.sg/luakt/paper/SUB01.ps BASE Show details 48 Line and Word Segmentation of . . . G. Louloudis; B. Gatos; I. Pratikakis... In: http://www.iit.demokritos.gr/~bgat/cr1115.pdf BASE Show details 49 Which is More Suitable for Chinese Word Segmentation, the Generative Model or the Discriminative One? F∗ Kun Wang A; Chengqing Zong A; Keh-yih Su B In: http://www.aclweb.org/anthology-new/Y/Y09/Y09-2047.pdf BASE Show details 50 Comparing Different Criteria for Vietnamese Word Segmentation Quy T. Nguyen; Ngan L. T; Nguyen Y Miyao In: http://www.aclweb.org/anthology/W/W12/W12-5005.pdf BASE Show details 51 A Pragmatic Chinese Word Segmentation Approach Based on Mixing Models 1 Wei Jiang; Yi Guan; Xiao-long Wang In: http://www.aclclp.org.tw/clclp/v11n4/v11n4a5.pdf BASE Show details 52 Strategies of Processing Japanese Names and Character Variants in Traditional Chinese Text Chuan-jie Lin; Jia-cheng Zhan; Yen-heng Chen; Chien-wei Pao In: http://wing.comp.nus.edu.sg/~antho/O/O12/O12-4004.pdf Abstract: This paper proposes an approach to identify word candidates that are not Traditional Chinese, including Japanese names (written in Japanese Kanji or Traditional Chinese characters) and word variants, when doing word segmentation on Traditional Chinese text. When handling personal names, a probability model concerning formats of names is introduced. We also propose a method to map Japanese Kanji into the corresponding Traditional Chinese characters. The same method can also be used to detect words written in character variants. After integrating generation rules for various types of special words, as well as their probability models, the F-measure of our word segmentation system rises from 94.16 % to 96.06%. Another experiment shows that 83.18 % of the 862 Japanese names in a set of 109 human-annotated documents can be successfully detected. Keyword: Character Variants; Japanese Name Identification; Semantic Chinese Word Segmentation URL: http://wing.comp.nus.edu.sg/~antho/O/O12/O12-4004.pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.396.6985 BASE Hide details 53 Using Heuristics Based Approach for Segmentation and Recognition of Printed Arabic Characters Ihab Zaqout In: http://www.sersc.org/journals/IJAST/vol49/2.pdf BASE Show details 54 Chinese Word Auto-Confirmation System using a Hybrid Approach Abstract Jia-lin Tsai; Cheng-lung Sung; Wen-lian Hsu In: http://www.iis.sinica.edu.tw/IASL/webpdf/paper-2003-Chinese_Word_Auto-Confirmation_System_using_a_Hybrid_Approach.pdf BASE Show details 55 Bridging the gap between speech technology and natural language processing: an evaluation toolbox for term discovery systems Mark Johnson; Emmanuel Dupoux In: http://www.lscp.net/persons/dupoux/papers/Ludusan_VJGCJD_2014_Evaluation_toolbox_term_discovery.LREC.pdf BASE Show details 56 © The Association for Computational Linguistics and Chinese Language Processing Chinese Word Segmentation as Character Tagging Nianwen Xue In: http://www.aclclp.org.tw/clclp/v8n1/v8n1a2.pdf BASE Show details 57 Ó The Association for Computational Linguistics and Chinese Language Processing Nianwen Xue In: http://verbs.colorado.edu/~xuen/publications/clclp03.xue.pdf BASE Show details 58 Storage and Retrieval]: Content Analysis and Indexing – Linguistic processing. Xin-jing Wang In: http://www2007.org/posters/poster923.pdf BASE Show details 59 Speech- and sound-segmentation in dyslexia: evidence for a multiple-level cortical impairment T. Kujala; J. Halmetoja; P. Alku... In: http://neuroscience.aecom.yu.edu/labs/sussmanlab/Pubs/Kujala_dyslexia.pdf BASE Show details 60 It’s Lawrence Phillips; Lisa Pearl In: http://www.socsci.uci.edu/~lpearl/papers/PhillipsPearl2014_ReasonableErrorsWordSegCogSci.pdf BASE Show details Page: 1 2 3 4

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