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Multilingual Part-of-Speech Tagging: Two Unsupervised Approaches
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In: http://dspace.mit.edu/openaccess-disseminate/1721.1/62804/ (2014)
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| 2 |
Adding more languages improves unsupervised multilingual tagging
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In: http://newdesign.aclweb.org/anthology-new/N/N09/N09-1010.pdf (2009)
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| 3 |
Adding more languages improves unsupervised multilingual tagging
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In: http://www.mt-archive.info/NAACL-HLT-2009-Snyder.pdf (2009)
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| 4 |
Multilingual part-of-speech tagging: Two unsupervised approaches
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In: http://www.jair.org/media/2843/live-2843-4725-jair.pdf (2009)
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| 5 |
Adding more languages improves unsupervised multilingual part-of-speech tagging: A bayesian non-parametric approach
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In: http://people.csail.mit.edu/regina/my_papers/pos.pdf (2009)
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| 6 |
Bayesian unsupervised topic segmentation
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In: http://www.aclweb.org/anthology-new/D/D08/D08-1035.pdf (2008)
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| 7 |
Gesture in Automatic Discourse Processing
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In: http://www.ai.mit.edu/projects/rationale/publications/Eisenstein2008Thesis.pdf (2008)
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| 8 |
Unsupervised multilingual learning for pos tagging
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In: http://www.aclweb.org/anthology-new/D/D08/D08-1109.pdf (2008)
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| 9 |
Discourse topic and gestural form
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In: http://www.aaai.org/Papers/AAAI/2008/AAAI08-133.pdf (2008)
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| 10 |
Discourse topic and gestural form
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In: http://rationale.csail.mit.edu/publications/Eisenstein2008Discourse.pdf (2008)
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Abstract:
Coverbal gesture provides a channel for the visual expression of ideas. While some gestural emblems have culturally predefined forms (e.g., “thumbs up”), the relationship between gesture and meaning is, in general, not conventionalized. It is natural to ask whether such gestures can be interpreted in a speaker-independent way, or whether gestural form is determined by the speaker’s idiosyncratic view of the discourse topic. We address this question using an audiovisual dataset across multiple speakers and topics. Our analysis employs a hierarchical Bayesian author-topic model, in which gestural patterns are stochastically generated by a mixture of speaker-specific and topic-specific priors. These gestural patterns are characterized using automaticallyextracted visual features, based on spatio-temporal interest points. This framework detects significant crossspeaker patterns in gesture that are governed by the discourse topic, suggesting that even unstructured gesticulation can be interpreted across speakers. In addition, the success of this approach shows that the semantic characteristics of gesture can be detected via a lowlevel, interest point representation.
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.379.8778
http://rationale.csail.mit.edu/publications/Eisenstein2008Discourse.pdf
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| 11 |
Discourse topic and gestural form
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In: http://people.csail.mit.edu/jacobe/papers/DTGF_AAAI2008.pdf (2008)
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| 12 |
Discourse topic and gestural form
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In: http://www.ai.mit.edu/projects/rationale/publications/Eisenstein2008DiscourseTopic.pdf (2008)
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| 13 |
Gesture in Automatic Discourse Processing
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In: http://people.csail.mit.edu/jacobe/papers/diss.pdf (2008)
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| 14 |
Gestural Cohesion for Topic Segmentation
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In: http://people.csail.mit.edu/jacobe/papers/GCTS_ACL2008.pdf
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| 15 |
Bayesian Unsupervised Topic Segmentation
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In: http://people.csail.mit.edu/jacobe/papers/EMNLP_BUTS.pdf
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| 16 |
Gestural Cohesion for Topic Segmentation
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In: http://www.csail.mit.edu/~jacobe/papers/Eisenstein08Gestural.pdf
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| 17 |
Gestural Cohesion for Topic Segmentation
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In: http://aclweb.org/anthology-new/P/P08/P08-1097.pdf
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| 18 |
Gestural Cohesion for Topic Segmentation
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In: http://www.ai.mit.edu/projects/rationale/publications/Eisenstein2008GesturalCohesion.pdf
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| 19 |
Unsupervised Multilingual Learning for POS Tagging
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In: http://people.csail.mit.edu/jacobe/papers/EMNLP_POS.pdf
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| 20 |
Modeling gesture salience as a hidden variable for coreference resolution and keyframe extraction
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In: http://www.aaai.org/Papers/JAIR/Vol31/JAIR-3111.pdf
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