Book contents
- Dimensions of Phonological Stress
- Dimensions of Phonological Stress
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Introduction
- 1 Metrical Incoherence: Diachronic Sources and Synchronic Analysis
- 2 The Role of Phenomenal Accent
- 3 Foot Alignment in Spanish Secondary Stress
- 4 The Interaction of Metrical Structure and Tone in Standard Chinese
- 5 Prominence, Contrast, and the Functional Load Hypothesis: An Acoustic Investigation
- 6 Iquito: The Prosodic Colon and Evaluation of OT Stress Accounts
- 7 Investigating the Efficiency of Parsing Strategies for the Gradual Learning Algorithm
- 8 Covert Representations, Contrast, and the Acquisition of Lexical Accent
- 9 One or Many? In Search of the Default Stress in Greek
- 10 The Development of Rhythmic Preferences by Dutch-learning Infants
- 11 Acoustic Characteristics of Infant-directed Speech as a Function of Prosodic Typology
- Index
- References
7 - Investigating the Efficiency of Parsing Strategies for the Gradual Learning Algorithm
Published online by Cambridge University Press: 25 November 2016
By
Book contents
- Dimensions of Phonological Stress
- Dimensions of Phonological Stress
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Introduction
- 1 Metrical Incoherence: Diachronic Sources and Synchronic Analysis
- 2 The Role of Phenomenal Accent
- 3 Foot Alignment in Spanish Secondary Stress
- 4 The Interaction of Metrical Structure and Tone in Standard Chinese
- 5 Prominence, Contrast, and the Functional Load Hypothesis: An Acoustic Investigation
- 6 Iquito: The Prosodic Colon and Evaluation of OT Stress Accounts
- 7 Investigating the Efficiency of Parsing Strategies for the Gradual Learning Algorithm
- 8 Covert Representations, Contrast, and the Acquisition of Lexical Accent
- 9 One or Many? In Search of the Default Stress in Greek
- 10 The Development of Rhythmic Preferences by Dutch-learning Infants
- 11 Acoustic Characteristics of Infant-directed Speech as a Function of Prosodic Typology
- Index
- References
- Type
- Chapter
- Information
- Dimensions of Phonological Stress , pp. 201 - 230Publisher: Cambridge University PressPrint publication year: 2016
References
Akers, Crystal. 2011. Simultaneous Learning of Hidden Linguistic Structures. PhD dissertation, Rutgers University, New Brunswick, NJ.Google Scholar
Alderete, John, Brasoveanu, Adrian, Merchant, Nazarré, Prince, Alan and Tesar, Bruce. 2005. Contrast Analysis Aids the Learning of Phonological Underlying Forms. In Han, Chung-hye and Kochetov, Alexei (eds.), Proceedings of the 24th West Coast Conference on Formal Linguistics, 34–42. Somerville, MA: Cascadilla Proceedings Project.Google Scholar
Apoussidou, Diana. 2006. On-line Learning of Underlying Forms. University of Amsterdam, ms.Google Scholar
Apoussidou, Diana. 2007. The Learnability of Metrical Phonology. PhD dissertation, University of Amsterdam.Google Scholar
Apoussidou, Diana and Boersma, Paul. 2003. The learnability of Latin Stress. IFA Proceedings 25. University of Amsterdam. 101–148.Google Scholar
Bane, Max and Riggle, Jason. To appear. The Typological Consequences of Weighted Constraints. In Proceedings of the Forty-Fifth Meeting of the Chicago Linguistic Society (2009).Google Scholar
Biró, Tamás.2013. Towards a Robuster Interpretive Parsing, Learning from overt forms in Optimality Theory. Journal of Logic, Language and Information 22. 139–172.CrossRefGoogle Scholar
Boersma, Paul. 1997. How We Learn Variation, Optionality, and Probability. IFA Proceedings 21. University of Amsterdam. 43–58.Google Scholar
Boersma, Paul. 2003. Review of Tesar & Smolensky (2000): Learnability in Optimality Theory. Phonology 20(3). 436–446.CrossRefGoogle Scholar
Boersma, Paul and Hayes, Bruce. 2001. Empirical Tests of the Gradual Learning Algorithm. Linguistic Inquiry 32(1). 45–86.CrossRefGoogle Scholar
Boersma, Paul and Levelt, Claartje. 2000. Gradual Constraint-Ranking Learning Algorithm Predicts Acquisition Order. In Proceedings of 30th Child Language Research Forum, 229–237. Stanford, CA: CSLI.Google Scholar
Boersma, Paul and Pater, Joe. 2013. Convergence Properties of a Gradual Learning Algorithm for Harmonic Grammar. Unpublished paper.Google Scholar
Boersma, Paul and Pater, Joe. To appear. Convergence Properties of a Gradual Learning Algorithm for Harmonic Grammar. In McCarthy, John (ed.), Harmonic Grammar and Harmonic Serialism. London: Equinox Press.Google Scholar
Coetzee, Andries and Pater, Joe. 2008a. Weighted Constraints and Gradient Restrictions on Place Co-occurrence in Muna and Arabic. Natural Language & Linguistic Theory 26(2). 289–337.CrossRefGoogle Scholar
Coetzee, Andries and Pater, Joe. 2008b. The Place of Variation in Phonological Theory. In Goldsmith, John, Riggle, Jason and Yu, Alan (eds.), The Handbook of Phonological Theory. 2nd edition. Oxford: Wiley Blackwell.Google Scholar
Daland, Robert, Hayes, Bruce, White, James, Garellek, Marc, Davis, Andrea and Norrmann, Ingrid. 2011. Explaining Sonority Projection Effects. Phonology 28(2). 197–234.Google Scholar
Dresher, B. Elan. 1999. Charting the Learning Path: Cues to Parameter Setting. Linguistic Inquiry 30(1). 27–67.CrossRefGoogle Scholar
Dresher, B. Elan and Kaye, Jonathan D. 1990. A Computational Learning Model for Metrical Phonology. Cognition 34(2). 137–195.CrossRefGoogle ScholarPubMed
Fischer, Marcus. 2005. A Robbins-Monro Type Learning Algorithm for an Entropy Maximizing Version of Stochastic Optimality Theory. Master’s Thesis, Humboldt University, Berlin.Google Scholar
Goldsmith, John. 1994. A Dynamic Computational Theory of Accent Systems. In Cole, Jennifer and Kisseberth, Charles (eds.), Perspectives in Phonology, 1–28. Stanford, CA: CSLI.Google Scholar
Goldwater, Sharon and Johnson, Mark. 2003. Learning OT Constraint Rankings Using a Maximum Entropy Model. In Proceedings of the Workshop on Variation within Optimality Theory. Stockholm University.Google Scholar
Gordon, Matthew. 2002. A Factorial Typology of Quantity-Insensitive Stress. Natural Language & Linguistic Theory 20(3). 491–552.CrossRefGoogle Scholar
Hammond, Michael. 2004. Gradience, Phonotactics, and the Lexicon in English Phonology. International Journal of English Studies 4. 1–24.Google Scholar
Hayes, Bruce. 1995. Metrical Stress Theory: Principles and Case Studies. Chicago: University of Chicago Press.Google Scholar
Hayes, Bruce. 2004. Phonological Acquisition in Optimality Theory: The Early Stages. In Kager, René, Pater, Joe and Zonneveld, Wim (ed.), Fixing Priorities: Constraints in Phonological Acquisition, 245–291. Cambridge: Cambridge University Press.Google Scholar
Hayes, Bruce and Londe, Zsuzsa Cziraky. 2006. Stochastic Phonological Knowledge: The Case of Hungarian Vowel Harmony. Phonology 23(01). 59–104.CrossRefGoogle Scholar
Hayes, Bruce and Wilson, Colin. 2008. A Maximum Entropy Model of Phonotactics and Phonotactic Learning. Linguistic Inquiry 39(3). 379–440.CrossRefGoogle Scholar
Hayes, B., Zuraw, K., Siptár, P. and Londe, Z. 2008. Natural and Unnatural Constraints in Hungarian Vowel Harmony. Language 85. 822–863.CrossRefGoogle Scholar
Heinz, Jeffrey. 2009. On the Role of Locality in Learning Stress Patterns. Phonology 26(02). 303–351.CrossRefGoogle Scholar
Jarosz, Gaja. 2006a. Rich Lexicons and Restrictive Grammars – Maximum Likelihood Learning in Optimality Theory. PhD dissertation, the Johns Hopkins University, Baltimore, MD.Google Scholar
Jarosz, Gaja. 2006b. Richness of the Base and Probabilistic Unsupervised Learning in Optimality Theory. In Proceedings of the Eighth Meeting of the ACL Special Interest Group on Computational Phonology at HLT-NAACL, 50–59. New York: Association for Computational Linguistics.Google Scholar
Jarosz, Gaja. 2010. Implicational Markedness and Frequency in Constraint-Based Computational Models of Phonological Learning. Journal of Child Language. Special Issue on Computational Models of Child Language Learning 37(3). 565–606.Google ScholarPubMed
Jarosz, Gaja. 2013a. Learning with Hidden Structure in Optimality Theory and Harmonic Grammar: Beyond Robust Interpretive Parsing. Phonology 30(1). 27–71.CrossRefGoogle Scholar
Jarosz, Gaja. 2013b. Naive Parameter Learning for Optimality Theory – The Hidden Structure Problem. In Kan, Seda, Moore-Cantwell, Claire and Staubs, Robert (eds.), Proceedings of the 40th Annual Meeting of the North East Linguistic Society, vol. 2, 1–14. Amherst, MA: GLSA.Google Scholar
Jäger, Gerhard. 2007 . Maximum Entropy Models and Stochastic Optimality Theory. In Zaenen, Annie, Simpson, Jane, King, Tracy Holloway, Grimshaw, Jane, Maling, Joan and Manning, Chris (eds.), Architectures, Rules, and Preferences: Variation on Themes by Joan Bresnan, 467–479. Stanford, CA: CSLI Publications.Google Scholar
Jesney, Karen and Tessier, Anne-Michelle. 2011. Biases in Harmonic Grammar: The Road to Restrictive Learning. Natural Language and Linguistic Theory 29(1). 251–290.CrossRefGoogle Scholar
Keller, Frank. 2000. Gradience in Grammar: Experimental and Computational Aspects of Degrees of Grammaticality. PhD dissertation, University of Edinburgh.Google Scholar
Legendre, Geraldine, Miyata, Yoshiro and Smolensky, Paul. 1990. Can Connectionism Contribute to Syntax? Harmonic Grammar, with an Application. CLS 26(1). 237–252.Google Scholar
Legendre, Géraldine, Sorace, Antonella and Smolensky, Paul. 2006. The Optimality Theory – Harmonic Grammar Connection. In Smolensky, Paul and Legendre, Géraldine (eds.), The Harmonic Mind: From Neural Computation to Optimality-Theoretic Grammar. Cambridge, MA: MIT Press.Google Scholar
Liberman, Mark and Prince, Allen. 1977. On Stress and Linguistic Rhythm. Linguistic Inquiry 8. 249–336.Google Scholar
Martin, Andrew. 2011. Grammars Leak: Modeling How Phonotactic Generalizations Interact within the Grammar. Language 87(4). 751–770.CrossRefGoogle Scholar
McCarthy, John J and Prince, Alan. 1993. Generalized Alignment. In Booij, Geert E and van Marle, J (eds.), Yearbook of Morphology, 79–153. Dordrecht: Kluwer.Google Scholar
Merchant, Nazarré. 2008. Discovering Underlying Forms: Contrast Pairs and Ranking. PhD dissertation, Rutgers University, New Brunswick, NJ.Google Scholar
Merchant, Nazarré and Tesar, Bruce. 2008. Learning Underlying Forms by Searching Restricted Lexical Subspaces. In Proceedings of the Forty-First Conference of the Chicago Linguistic Society, 33–47. Chicago Linguistics Society.Google Scholar
Pater, Joe. 2009. Weighted Constraints in Generative Linguistics. Cognitive Science 33. 999–1035.CrossRefGoogle ScholarPubMed
Pater, Joe. 2014. Canadian Raising with Language-Specific Weighted Constraints. Language 90(1). 230–240.CrossRefGoogle Scholar
Potts, Christopher, Pater, Joe, Jesney, Karen, Bhatt, Rajesh and Becker, Michael. 2010. Harmonic Grammar with Linear Programming: From Linear Systems to Linguistic Typology. Phonology 27(1). 1–41.CrossRefGoogle Scholar
Prince, Allen. 1990. Quantitative Consequences of Rhythmic Organization. In Deaton, K, Noske, M and Ziolkowski, M (eds.), CLS26-II: Papers from the Parasession on the Syllable in Phonetics and Phonology. Chicago Linguistic Society 26. 355–398.Google Scholar
Prince, Alan and Smolensky, Paul. 1993. Optimality Theory: Constraint Interaction in Generative Grammar. Tech. Rep. 2, Rutgers University Center for Cognitive Science.Google Scholar
Prince, Alan and Smolensky, Paul. 2004. Optimality Theory: Constraint Interaction in Generative Grammar. Malden, MA: Blackwell.CrossRefGoogle Scholar
Rosenblatt, Frank. 1958. The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain. Psychological Review 65. 386–408.CrossRefGoogle ScholarPubMed
Smolensky, Paul. 1996. The Initial State and “Richness of the Base”. Johns Hopkins University, Baltimore, MD: Technical Report JHU-CogSci-96-4, ms.Google Scholar
Smolensky, Paul and Legendre, Géraldine. 2006. The Harmonic Mind: From Neural Computation to Optimality-theoretic Grammar. Cambridge, MA: MIT Press.Google Scholar
Tesar, Bruce. 1995. Computational Optimality Theory. PhD dissertation. Boulder, CO: University of Colorado.Google Scholar
Tesar, Bruce. 1997. Multi-Recursive Constraint Demotion. New Brunswick, NJ: Rutgers University.Google Scholar
Tesar, Bruce. 2000. Using Inconsistency Detection to Overcome Structural Ambiguity in Language Learning. Using Inconsistency Detection to Overcome Structural Ambiguity in Language Learning. Technical Report RuCCS-TR-58, Rutgers Center for Cognitive Science, Rutgers University, ms.Google Scholar
Tesar, Bruce. 2004a. Contrast Analysis in Phonological Learning. Rutgers University, NJ, ms.Google Scholar
Tesar, Bruce. 2004b. Using Inconsistency Detection to Overcome Structural Ambiguity. Linguistic Inquiry 35(2). 219–253.CrossRefGoogle Scholar
Tesar, Bruce. 2006a. Faithful Contrastive Features in Learning. Cognitive Science 30(5). 863–903.CrossRefGoogle ScholarPubMed
Tesar, Bruce. 2006b. Learning from Paradigmatic Information. In Proceedings of the Thirty-Sixth Conference of the North East Linguistics Society, University of Massuchssetts, October 28–30, 2005, 619–638.Google Scholar
Tesar, Bruce. 2009. Learning Phonological Grammars for Output-Driven Maps. In Proceedings of the Thirty-Ninth Conference of the North East Linguistics Society, Cornell University, November 7–9, 2008.Google Scholar
Tesar, Bruce, Alderete, John, Horwood, Graham, Merchant, Nazarré, Nishitani, Koichi and Prince, Alan. 2003. Surgery in Language Learning. In Proceedings of the 22nd West Coast Conference on Formal Linguistics, 477–490.Google Scholar
Tesar, Bruce and Smolensky, Paul. 1998. Learnability in Optimality Theory. Linguistic Inquiry 29(2). 229–268.CrossRefGoogle Scholar
Tesar, Bruce and Smolensky, Paul. 2000. Learnability in Optimality Theory. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Tessier, Anne-Michelle. 2009. Frequency of Violation and Constraint-based Phonological Learning. Lingua 119(1). 6–38.CrossRefGoogle Scholar
Wexler, Kenneth and Culicover, Peter. 1980. Formal Principles of Language Acquisition. Cambridge, MA: MIT Press.Google Scholar
Wilson, Colin. 2006. Learning Phonology With Substantive Bias: An Experimental and Computational Study of Velar Palatalization. Cognitive Science 30(5). 945–982.CrossRefGoogle ScholarPubMed