Work

Speech perception: a model of word recognition

Year: 2025

Type: article

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

Source: The European Physical Journal B

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

Authors: Jean-Marc Luck, Anita Mehta

Institutions: Centre National de la Recherche Scientifique, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Université Paris-Saclay, Institut de Physique Théorique, University of Oxford

Language: English

Topic: Speech Recognition and Synthesis

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,490

Funders: Leverhulme Trust, Université Paris-Saclay