Speech perception: a model of word recognition

Jean-Marc Luck () and Anita Mehta ()
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Jean-Marc Luck: Université Paris-Saclay, CNRS & CEA
Anita Mehta: Clarendon Institute, Walton Street

The European Physical Journal B: Condensed Matter and Complex Systems, 2025, vol. 98, issue 2, 1-18

Abstract: Abstract We present a model of speech perception which takes into account effects o correlations between sounds. Words in this model correspond to the attractors of a suitably chosen descent dynamics. The resulting lexicon is rich in short words, and much less so in longer ones, as befits a reasonable word length distribution. We separately examine the decryption of short and long words in the presence of mishearings. In the regime of short words, the algorithm either quickly retrieves a word, or proposes another valid word. In the regime of longer words, the behaviour is markedly different. While the successful decryption of words continues to be relatively fast, there is a finite probability of getting lost permanently, as the algorithm wanders round the landscape of suitable words without ever settling on one. Graphic abstract

Date: 2025
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DOI: 10.1140/epjb/s10051-025-00882-w

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