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Optimality Theory: Constraint Interaction in Generative Grammar ...
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Compositional processing emerges in neural networks solving math problems
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In: Proceedings of the Annual Meeting of the Cognitive Science Society, vol 43, iss 43 (2021)
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Infinite use of finite means? Evaluating the generalization of center embedding learned from an artificial grammar
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In: Proceedings of the Annual Meeting of the Cognitive Science Society, vol 43, iss 43 (2021)
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Compositional Processing Emerges in Neural Networks Solving Math Problems ...
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Distributed neural encoding of binding to thematic roles ...
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Infinite use of finite means? Evaluating the generalization of center embedding learned from an artificial grammar ...
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Compositional processing emerges in neural networks solving math problems ...
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How much do language models copy from their training data? Evaluating linguistic novelty in text generation using RAVEN ...
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Compositional Processing Emerges in Neural Networks Solving Math Problems
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In: Cogsci (2021)
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Emergent Gestural Scores in a Recurrent Neural Network Model of Vowel Harmony
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In: Proceedings of the Society for Computation in Linguistics (2021)
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Abstract:
In this paper, we present the results of neural network modeling of speech production. We introduce GestNet, a sequence-to-sequence, encoder-decoder neural network architecture in which a string of input symbols is translated into sequences of vocal tract articulator movements. We train our models to produce movements of lip and tongue body articulators consistent with a pattern of stepwise vowel height harmony. Though we provide our models with no linguistic structure, they reliably learn this harmony pattern. In addition, by probing these models we find evidence of emergent linguistic structure. Specifically, we examine patterns of encoder-decoder attention (degree of influence of specific input segments on model outputs) and find that they resemble the patterns of gestural activation assumed within the Gestural Harmony Model, a model of harmony built upon the representations of Articulatory Phonology. This result is significant as it lends support to one of the central claims of the Gestural Harmony Model: that harmony is the result of the harmony-triggering gestures extending to overlap the gestures of surrounding segments.
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Keyword:
Computational Linguistics; gestural phonology; neural network; RNN; speech production; vowel harmony
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URL: https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1226&context=scil https://scholarworks.umass.edu/scil/vol4/iss1/7
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Testing for Grammatical Category Abstraction in Neural Language Models
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In: Proceedings of the Society for Computation in Linguistics (2021)
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Universal linguistic inductive biases via meta-learning ...
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Tensor Product Decomposition Networks: Uncovering Representations of Structure Learned by Neural Networks
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In: Proceedings of the Society for Computation in Linguistics (2020)
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Learning a gradient grammar of French liaison
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In: Proceedings of the Annual Meetings on Phonology; Proceedings of the 2019 Annual Meeting on Phonology ; 2377-3324 (2020)
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RNNs Implicitly Implement Tensor Product Representations
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In: International Conference on Learning Representations ; ICLR 2019 - International Conference on Learning Representations ; https://hal.archives-ouvertes.fr/hal-02274498 ; ICLR 2019 - International Conference on Learning Representations, May 2019, New Orleans, United States (2019)
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Transient blend states and discrete agreement-driven errors in sentence production
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In: Proceedings of the Society for Computation in Linguistics (2019)
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Augmentic Compositional Models for Knowledge Base Completion Using Gradient Representations
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In: Proceedings of the Society for Computation in Linguistics (2019)
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Augmenting Compositional Models for Knowledge Base Completion Using Gradient Representations ...
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A Simple Recurrent Unit with Reduced Tensor Product Representations ...
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