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POS induction with distributional and morphological information using a distance-dependent Chinese Restaurant Process
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Semantic title evaluation and recommendation based on topic models
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A Summary of the 2012 JHU CLSP workshop on zero resource speech technologies and models of early language acquisition
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Jansen, Aren; Dupoux, Emmanuel; Seltzer, Mike; Clark, Pascal; McGraw, Ian; Varadarajan, Balakrishnan; Bennett, Erin; Borschinger, Benjamin; Chiu, Justin; Dunbar, Ewan; Fourtassi, Abdellah; Harwath, David; Goldwater, Sharon; Lee, Chia-ying; Levin, Keith; Norouzian, Atta; Peddinti, Vijayaditya; Richardson, Rachael; Schatz, Thomas; Thomas, Samuel; Johnson, Mark; Khudanpur, Sanjeev; Church, Kenneth; Feldman, Naomi; Hermansky, Hynek; Metze, Florian; Rose, Richard. - : Piscataway, NJ : IEEE, 2013
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Abstract:
We summarize the accomplishments of a multi-disciplinary workshop exploring the computational and scientific issues surrounding zero resource (unsupervised) speech technologies and related models of early language acquisition. Centered around the tasks of phonetic and lexical discovery, we consider unified evaluation metrics, present two new approaches for improving speaker independence in the absence of supervision, and evaluate the application of Bayesian word segmentation algorithms to automatic subword unit tokenizations. Finally, we present two strategies for integrating zero resource techniques into supervised settings, demonstrating the potential of unsupervised methods to improve mainstream technologies. ; 5 page(s)
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Keyword:
080100 Artificial Intelligence and Image Processing
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URL: http://hdl.handle.net/1959.14/265207
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Whyisenglishsoeasytosegment? ; Why is English so easy to segment?
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Dynamic 3-D visualization of vocal tract shaping during speech
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Working with a small dataset - semi-supervised dependency parsing for Irish
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A Joint model of word segmentation and phonological variation for English word-final t-deletion
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Parsing entire discourses as very long strings : capturing topic continuity in grounded language learning
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A Non-monotonic Arc-Eager transition system for dependency parsing
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Modeling graph languages with grammars extracted via tree decompositions
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Learning from OzCLO, the Australian Computational and Linguistics Olympiad
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The effect of non-tightness on Bayesian estimation of PCFGs
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Exploring adaptor grammars for native language identification
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