RT info:eu-repo/semantics/article
T1 Prosodic feature analysis for automatic speech assessment and individual report generation in people with Down syndrome
A1 Corrales Astorgano, Mario
A1 González Ferreras, César
A1 Escudero Mancebo, David
A1 Cardeñoso Payo, Valentín
K1 Down syndrome
K1 Down, Síndrome de
K1 Medical genetics
K1 Genética
K1 Prosody
K1 Prosodia
K1 Speech processing systems
K1 Síntesis automática del habla
K1 Computational linguistics
K1 Technology
K1 Science
K1 57 Lingüística
K1 5701.04 Lingüística Informatizada
K1 33 Ciencias Tecnológicas
AB Evaluating prosodic quality poses unique challenges due to the intricate nature of prosody, which encompasses multiple form–function profiles. These challenges are more pronounced when analyzing the voices of individuals with Down syndrome (DS) due to increased variability. This paper introduces a procedure for selecting informative prosodic features based on both the disparity between human-rated DS productions and their divergence from the productions of typical users, utilizing a corpus constructed through a video game. Individual reports of five speakers with DS are created by comparing the selected features of each user with recordings of individuals without intellectual disabilities. The acquired features primarily relate to the temporal domain, reducing dependence on pitch detection algorithms, which encounter difficulties when dealing with pathological voices compared to typical ones. These individual reports can be instrumental in identifying specific issues for each speaker, assisting therapists in defining tailored training sessions based on the speaker’s profile.
PB MDPI
SN 2076-3417
YR 2023
FD 2023
LK https://uvadoc.uva.es/handle/10324/67234
UL https://uvadoc.uva.es/handle/10324/67234
LA eng
NO Applied Sciences, 2024, Vol. 14, Nº. 1, 293
NO Producción Científica
DS UVaDOC
RD 18-may-2024