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101 |
How Well Do LSTM Language Models Learn Filler-gap Dependencies?
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In: Proceedings of the Society for Computation in Linguistics (2022)
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102 |
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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103 |
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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104 |
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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105 |
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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106 |
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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107 |
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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108 |
Representing Multiple Dependencies in Prosodic Structures
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In: Proceedings of the Society for Computation in Linguistics (2022)
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109 |
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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110 |
Concurrent hidden structure & grammar learning
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In: Proceedings of the Society for Computation in Linguistics (2022)
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111 |
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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112 |
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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Abstract:
While corpora of child speech and child-directed speech (CDS) have enabled major contributions to the study of child language acquisition, semantic annotation for such corpora is still scarce and lacks a uniform standard. We compile two CDS corpora—in English and Hebrew—with syntactic and semantic annotations. We employ a methodology that enforces a cross-linguistically consistent representation, building on recent advances in dependency representation and semantic parsing. Our semi-automatic syntactic annotation follows the Universal Dependencies standard (UD; de Marneffe et al., 2021), adapted to suit the CDS genre. To induce semantic forms, we develop an automatic method for transducing UD structures into sentential logical forms (LFs). The two representations have complementary strengths: UD structures are language-neutral and support direct annotation, whereas LFs are neutral as to the syntax-semantics interface, and transparently encode semantic distinctions.
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Keyword:
child-directed speech; Computational Linguistics; corpus annotation; language acquisition; syntax-semantics interface; Universal Dependencies
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URL: https://scholarworks.umass.edu/scil/vol5/iss1/25 https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1254&context=scil
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113 |
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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114 |
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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115 |
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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116 |
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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117 |
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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118 |
Remodelling complement coercion interpretation
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In: Proceedings of the Society for Computation in Linguistics (2022)
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119 |
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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120 |
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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