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1
Early Tashelhiyt Berber word segmentation: the role of the Possible Word Constraint ...
Elouatiq, Abdellah. - : Open Science Framework, 2021
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2
Auditory disruption improves word segmentation: A functional basis for lenition phenomena
In: Glossa: a journal of general linguistics; Vol 3, No 1 (2018); 38 ; 2397-1835 (2018)
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3
Segmentation of vowel-initial words is facilitated by function words
Kim, Yun Jung. - : eScholarship, University of California, 2012
In: Kim, Yun Jung. (2012). Segmentation of vowel-initial words is facilitated by function words. UCLA: Linguistics 0510. Retrieved from: http://www.escholarship.org/uc/item/7v8573tk (2012)
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4
Segmentation of vowel-initial words is facilitated by function words
Kim, Yun Jung. - : eScholarship, University of California, 2012
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5
Segmentation of vowel-initial words is facilitated by function words
Kim, Yun Jung. - : eScholarship, University of California, 2012
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6
A Formal Model of Ambiguity and its Applications in Machine Translation
In: DTIC (2010)
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7
Portable Language-Independent Adaptive Translation From OCR
In: DTIC (2009)
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8
Portable Language-Independent Adaptive Translation from OCR
In: DTIC (2009)
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9
Portable Language-Independent Adaptive Translation from OCR. Phase 1
In: DTIC (2009)
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10
Hybrid models for Chinese unknown word resolution
In: http://rave.ohiolink.edu/etdc/view?acc_num=osu1154631880 (2006)
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11
Investigation on Mandarin Broadcast News Speech Recognition
In: DTIC (2006)
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12
A Methodology for End-to-End Evaluation of Arabic Document Image Processing Software
In: DTIC (2006)
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13
The Slaying of Lady Mondegreen, being a Study of French Tonal Association and Alignment and their Role in Speech Segmentation
In: http://rave.ohiolink.edu/etdc/view?acc_num=osu1074614793 (2003)
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14
HowtogetaChineseName(Entity): Segmentation and Combination Issues
In: DTIC (2003)
Abstract: When building a Chinese named entity recognition system, one must deal with certain language-specific issues such as whether the model should be based on characters or words. While there is no unique answer to this question, we discuss in detail advantages and disadvantages of each model, identify problems in segmentation and suggest possible solutions, presenting our observations, analysis, and experimental results. The second topic of this paper is classifier combination. We present and describe four classifiers for Chinese named entity recognition and describe various methods for combining their outputs. The results demonstrate that classifier combination is an effective technique of improving system performance: experiments over a large annotated corpus of fine-grained entity types exhibit a 10% relative reduction in F-measure error. ; Presented at the Conference on Empirical Methods in Natural Language Processing (EMNLP 2003) held in Sapporo, Japan on 11-12 Jul 2003. Published in the Proceedings of the Conference on Empirical Methods in Natural Language Processing, 2003. Sponsored in part by DARPA and National Science Foundation.
Keyword: *CHINESE LANGUAGE; *CLASSIFIERS; *HMM(HIDDEN MARKOV MODEL); *NAMED ENTITY RECOGNITION; *RECOGNITION; *WORDS(LANGUAGE); ALGORITHMS; CHARACTER-BASED MODELS; CLASSIFICATION; Cybernetics; Information Science; Linguistics; MARKOV PROCESSES; MODELS; NATURAL LANGUAGE; SYMPOSIA; WORD SEGMENTATION; WORD-BASED MODELS
URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA457910
http://www.dtic.mil/docs/citations/ADA457910
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15
Nonword repetition and young children's receptive vocabulary: A longitudinal study
Bowey, Judith A.. - : Cambridge University Press, 2001
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