Evaluating AI supported ASR performance: the role of semantic density within the DLM
Abstract
AI-supported Automatic Speech Recognition (ASR) performance varies depending on age-related factors (e.g., Verhaeghen, 2003).Greater age → Bigger vocabulary → More meanings compete → More difficult to map word form onto meaning (i.e., greater semantic uncertainty)?A poor ASR performance may be due to increased uncertainty in the mapping between form and meaning.We test:whether semantic uncertainty predicts ASR performance.whether computational models with vocabularies representing different ages predict ASR performance more precisely.
Fields of Study & Subjects
Speech Recognition and Synthesis
Phonetics and Phonology Research
Neurobiology of Language and Bilingualism
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 26 February 2026
- Language
- EN