R. Harald Baayen
3 papers in the PaperMetrix corpus
Papers by this author
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Words from spontaneous conversational speech can be recognized with human-like accuracy by an error-driven learning algorithm that discriminates between meanings straight from smart acoustic features, bypassing the phoneme as recognition unit
2017 · PLoS ONE
Sound units play a pivotal role in cognitive models of auditory comprehension. The general consensus is that during perception listeners break down speech into auditory words and subsequently phones. Indeed, cognitive speech recognition is typically …
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LDL-AURIS: A computational model, grounded in error-driven learning, for the comprehension of single spoken words
2020
A computational model for auditory word recognition is presented that enhances the model of Arnold et al. (2017). Real-valued features are extracted from the speech signal instead of discrete features. One-hot encoding for words’ meanings …
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LDL-AURIS: a computational model, grounded in error-driven learning, for the comprehension of single spoken words
2021 · Language Cognition and Neuroscience
A computational model for the comprehension of single spoken words is presented that builds on an earlier model using discriminative learning. Real-valued features are extracted from the speech signal instead of discrete features. Vectors representing …