Konferenzbeitrag
Longitudinal study of voice recognition in children
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Datum
2020
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Verlag
Gesellschaft für Informatik e.V.
Zusammenfassung
Speaker recognition as a biometric modality is on the rise in the consumer marketplace
for banking, online services, and personal assistant services with a potential for wider application
areas. Most current applications involve adults. One of the biggest challenges in speaker recognition
for children is the change in the voice properties as a child age. This work proposes a baseline
longitudinal dataset from the same 30 children in the age group of 4 to 14 years over a time frame
of 2.5 years and evaluates speaker recognition performance in children with the available speaker
recognition technology.
Beschreibung
Schlagwörter
Speaker verification , Children’s voice , MFCC , LFCC , GMM , JFA , ISV , Inter-session
variability.