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Early Word Recognition and Later Language Skills
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In: Brain Sciences ; Volume 4 ; Issue 4 ; Pages 532-559 (2014)
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Bridging the gap between speech technology and natural language processing : an evaluation toolbox for term discovery systems
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Infants' Speech Segmentation: The Impact of Mother-Infant Facial Synchrony
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In: The Journal of Purdue Undergraduate Research (2014)
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Is Maternal Touch Used Referentially?
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In: Open Access Theses (2014)
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The Relationship between Implicit and Explicit Processing in Statistical Language Learning
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In: Electronic Thesis and Dissertation Repository (2014)
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Exploring Linguistic Constraints in Nlp Applications
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In: Publicly Accessible Penn Dissertations (2014)
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Abstract:
The key argument of this dissertation is that the success of an Natural Language Processing (NLP) application depends on a proper representation of the corresponding linguistic problem. This theme is raised in the context that the recent progress made in our field is widely credited to the effective use of strong engineering techniques. However, the intriguing power of highly lexicalized models shown in many NLP applications is not only an achievement by the development in machine learning, but also impossible without the extensive hand-annotated data resources made available, which are originally built with very deep linguistic considerations. More specifically, we explore three linguistic aspects in this dissertation: the distinction between closed-class vs. open-class words, long-tail distributions in vocabulary study and determinism in language models. The first two aspects are studied in unsupervised tasks, unsupervised part-of-speech (POS) tagging and morphology learning, and the last one is studied in supervised tasks, English POS tagging and Chinese word segmentation. Each linguistic aspect under study manifests itself in a (different) way to help improve performance or efficiency in some NLP application.
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Keyword:
Chinese word segmentation; closed-class words; Computer Sciences; long-tail distribution; Morphology learning; natural language processing; Unsupervised POS tagging
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URL: https://repository.upenn.edu/cgi/viewcontent.cgi?article=3335&context=edissertations https://repository.upenn.edu/edissertations/1523
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Traduction statistique vers une langue à morphologie riche : combinaison d’algorithmes de segmentation morphologique et de modèles statistiques de traduction automatique
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Seeing Spaces: An Eye-Tracking Study Of Speech Segmentation
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In: Honors Theses (2013)
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The neural correlates of statistical learning in a word segmentation task: An fMRI study
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In: ISSN: 0093-934X ; Brain and Language, Vol. 127, No 1 (2013) pp. 46-54 (2013)
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Analysis of language variation and word segmentation for a corpus of Vietnamese blogs ; a sociolinguistic approach
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Complexidade prosódica e segmentação de palavras em crianças dos 4 aos 6 anos de idade ; Prosodic complexity and word segmentation in children between 4 and 6 years old
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Infants generalize representations of statistically segmented words.
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WPP, No.111: Syllabification, Sonority, and Spoken Word Segmentation: Evidence from Word-Spotting
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In: Bishop, Jason; & Toda, Kristen. (2012). WPP, No.111: Syllabification, Sonority, and Spoken Word Segmentation: Evidence from Word-Spotting. UCLA: Department of Linguistics, UCLA. Retrieved from: http://www.escholarship.org/uc/item/2326q63g (2012)
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Segmentation of vowel-initial words is facilitated by function words
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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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Segmentation of vowel-initial words is facilitated by function words
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Segmentation of vowel-initial words is facilitated by function words
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Studying the effect of input size for Bayesian word segmentation on the providence corpus
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