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Universal Dependencies and Semantics for English and Hebrew Child-directed Speech
In: Proceedings of the Society for Computation in Linguistics (2022)
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.
Keyword: child-directed speech; Computational Linguistics; corpus annotation; language acquisition; syntax-semantics interface; Universal Dependencies
URL: https://scholarworks.umass.edu/scil/vol5/iss1/25
https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1254&context=scil
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2
Do Infants Really Learn Phonetic Categories?
In: EISSN: 2470-2986 ; Open Mind ; https://hal.archives-ouvertes.fr/hal-03550830 ; Open Mind, MIT Press, 2021, 5, pp.113-131. ⟨10.1162/opmi_a_00046⟩ (2021)
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Early phonetic learning without phonetic categories -- Insights from large-scale simulations on realistic input
In: ISSN: 0027-8424 ; EISSN: 1091-6490 ; Proceedings of the National Academy of Sciences of the United States of America ; https://hal.archives-ouvertes.fr/hal-03070566 ; Proceedings of the National Academy of Sciences of the United States of America , National Academy of Sciences, 2021, 118 (7), pp.e2001844118. ⟨10.1073/pnas.2001844118⟩ (2021)
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Black or White but never neutral: How readers perceive identity from yellow or skin-toned emoji ...
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5
A phonetic model of non-native spoken word processing ...
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6
Cross-linguistically Consistent Semantic and Syntactic Annotation of Child-directed Speech ...
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7
Do Infants Really Learn Phonetic Categories?
In: Open Mind (Camb) (2021)
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8
Early phonetic learning without phonetic categories: Insights from large-scale simulations on realistic input
In: Proc Natl Acad Sci U S A (2021)
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9
Multilingual acoustic word embedding models for processing zero-resource languages ...
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Improved acoustic word embeddings for zero-resource languages using multilingual transfer ...
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11
Analyzing autoencoder-based acoustic word embeddings ...
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Inflecting when there's no majority: Limitations of encoder-decoder neural networks as cognitive models for German plurals ...
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13
Evaluating computational models of infant phonetic learning across languages ...
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14
Multilingual and Unsupervised Subword Modeling for Zero-Resource Languages
In: http://infoscience.epfl.ch/record/277105 (2020)
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15
On understanding character-level models for representing morphology
Vania, Clara. - : The University of Edinburgh, 2020
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16
Methods for morphology learning in low(er)-resource scenarios
Bergmanis, Toms. - : The University of Edinburgh, 2020
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17
Discovering and analysing lexical variation in social media text
Shoemark, Philippa Jane. - : The University of Edinburgh, 2020
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18
Are we there yet? Encoder-decoder neural networks as cognitive models of English past tense inflection ...
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19
Analyzing ASR pretraining for low-resource speech-to-text translation ...
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20
Low-resource speech translation
Bansal, Sameer. - : The University of Edinburgh, 2019
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