• Corpus ID: 219176539

A Neural Network Model of Lexical Competition during Infant Spoken Word Recognition

@article{Duta2020ANN,
  title={A Neural Network Model of Lexical Competition during Infant Spoken Word Recognition},
  author={Mihaela D Duta and Kim Plunkett},
  journal={ArXiv},
  year={2020},
  volume={abs/2006.00999}
}
Visual world studies show that upon hearing a word in a target-absent visual context containing related and unrelated items, toddlers and adults briefly direct their gaze towards phonologically related items, before shifting towards semantically and visually related ones. We present a neural network model that processes dynamic unfolding phonological representations and maps them to static internal semantic and visual representations. The model, trained on representations derived from real… 

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A Neural Network Model of Lexical-Semantic Competition During Spoken Word Recognition

A neural network model is presented that processes dynamic unfolding phonological representations and maps them to static internal lexical, semantic and visual representations that capture the early phonological preference effects reported in a visual world task.

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