Automatic Evaluation of a Sentence Memory Test for Preschool Children

  • Assessment of memory capabilities in preschool-aged children is crucial for early detection of potential speech development impairments or delays. We present an approach for the automatic evaluation of a standardized sentence memory test specifically for preschool children. Our methodology leverages automatic transcription of recited sentences and evaluation based on natural language processing techniques. We demonstrate the effectiveness of our approach on a dataset comprised of recited sentences from preschool-aged children, incorporating ratings of semantic and syntactic correctness. The best performing systems achieve an F1 score of 91.7% for semantic correctness and 86.1% for syntactic correctness using automatic transcripts. Our results showcase the potential of automated evaluation systems in providing reliable and efficient assessments of memory capabilities in early childhood, facilitating timely interventions and support for children with language development needs.

Export metadata

Additional Services

Search Google Scholar
Metadaten
Author:Ilja BaumannORCiD, Nicole Unger, Dominik Wagner, Korbinian RiedhammerORCiD, Tobias BockletORCiD
DOI:https://doi.org/10.21437/Interspeech.2024-2125
Document Type:conference proceeding (article)
Language:English
Date of first Publication:2024/06/30
Release Date:2024/10/17
Tag:speech development, children’s speech, automatic assessment
Pagenumber:5
First Page:5158
Last Page:5162
Konferenzangabe:Interspeech 2024, 1 - 5 September, Kos, Greece
institutes:Zentrum für Künstliche Intelligenz (KIZ)
Research Themes:Digitalisierung & Künstliche Intelligenz
Verstanden ✔
Diese Webseite verwendet technisch erforderliche Session-Cookies. Durch die weitere Nutzung der Webseite stimmen Sie diesem zu. Unsere Datenschutzerklärung finden Sie hier.