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A split-gesture, competitive, coupled oscillator model of syllable structure predicts the emergence of edge gemination and degemination
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In: Proceedings of the Society for Computation in Linguistics (2022)
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102 |
Linguistic Complexity and Planning Effects on Word Duration in Hindi Read Aloud Speech
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In: Proceedings of the Society for Computation in Linguistics (2022)
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103 |
Learning Argument Structures with Recurrent Neural Network Grammars
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In: Proceedings of the Society for Computation in Linguistics (2022)
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104 |
MaxEnt Learners are Biased Against Giving Probability to Harmonically Bounded Candidates
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In: Proceedings of the Society for Computation in Linguistics (2022)
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105 |
Evaluating Structural Economy Claims in Relative Clause Attachment
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In: Proceedings of the Society for Computation in Linguistics (2022)
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106 |
A Model Theoretic Perspective on Phonological Feature Systems
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In: Proceedings of the Society for Computation in Linguistics (2022)
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107 |
Representing Multiple Dependencies in Prosodic Structures
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In: Proceedings of the Society for Computation in Linguistics (2022)
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108 |
Incremental Acquisition of a Minimalist Grammar using an SMT-Solver
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In: Proceedings of the Society for Computation in Linguistics (2022)
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109 |
Concurrent hidden structure & grammar learning
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In: Proceedings of the Society for Computation in Linguistics (2022)
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Abstract:
The concurrent learning of both unseen structures and grammar is an enduring problem in phonological acquisition. The present study develops a joint model of word-UR-SR triples that incorporates a Maximum Entropy model of SRs conditioned on URs. The learner was presented with word-SR frequencies, and successfully learned the hidden structures and grammars that enabled it to generalize well on test data that were withheld during training. When given an option between acquiring a grammar that supported a rich base analysis and one that didn’t, the learner always acquired the grammar that supported rich bases. These results suggest that the preference for acquiring a rich base grammar over a non rich base one is an emergent property of the proposed model.
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Keyword:
Computational Linguistics; hidden structure; maximum entropy; richness of the base; UR learning
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URL: https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1259&context=scil https://scholarworks.umass.edu/scil/vol5/iss1/5
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110 |
Can language models capture syntactic associations without surface cues? A case study of reflexive anaphor licensing in English control constructions
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In: Proceedings of the Society for Computation in Linguistics (2022)
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111 |
Universal Dependencies and Semantics for English and Hebrew Child-directed Speech
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In: Proceedings of the Society for Computation in Linguistics (2022)
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112 |
Learning Input Strictly Local Functions: Comparing Approaches with Catalan Adjectives
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In: Proceedings of the Society for Computation in Linguistics (2022)
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113 |
Learning Constraints on Wh-Dependencies by Learning How to Efficiently Represent Wh-Dependencies: A Developmental Modeling Investigation With Fragment Grammars
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In: Proceedings of the Society for Computation in Linguistics (2022)
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114 |
Typological Implications of Tier-Based Strictly Local Movement
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In: Proceedings of the Society for Computation in Linguistics (2022)
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115 |
Parsing Early Modern English for Linguistic Search
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In: Proceedings of the Society for Computation in Linguistics (2022)
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116 |
When Classifying Arguments, BERT Doesn't Care About Word Order. Except When It Matters
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In: Proceedings of the Society for Computation in Linguistics (2022)
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117 |
Remodelling complement coercion interpretation
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In: Proceedings of the Society for Computation in Linguistics (2022)
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118 |
Inferring Inferences: Relational Propositions for Argument Mining
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In: Proceedings of the Society for Computation in Linguistics (2022)
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119 |
ANLIzing the Adversarial Natural Language Inference Dataset
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In: Proceedings of the Society for Computation in Linguistics (2022)
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120 |
Analysis of Language Change in Collaborative Instruction Following
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In: Proceedings of the Society for Computation in Linguistics (2022)
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