TY - JOUR
T1 - Automatic assessment of prosodic quality in Down syndrome: Analysis of the impact of speaker heterogeneity
AU - Corrales-Astorgano, Mario
AU - Martínez-Castilla, Pastora
AU - Escudero-Mancebo, David
AU - Aguilar, Lourdes
AU - González-Ferreras, César
AU - Cardeñoso-Payo, Valentín
PY - 2019/4/1
Y1 - 2019/4/1
N2 - © 2019 by the authors. Prosody is a fundamental speech element responsible for communicative functions such as intonation, accent and phrasing, and prosodic impairments of individuals with intellectual disabilities reduce their communication skills. Yet, technological resources have paid little attention to prosody. This study aims to develop an automatic classifier to predict the prosodic quality of utterances produced by individuals with Down syndrome, and to analyse how inter-individual heterogeneity affects assessment results. A therapist and an expert in prosody judged the prosodic appropriateness of a corpus of Down syndrome' utterances collected through a video game. The judgments of the expert were used to train an automatic classifier that predicts prosodic quality by using a set of fundamental frequency, duration and intensity features. The classifier accuracy was 79.3% and its true positive rate 89.9%. We analyzed how informative each of the features was for the assessment and studied relationships between participants' developmental level and results: interspeaker variability conditioned the relative weight of prosodic features for automatic classification and participants' developmental level was related to the prosodic quality of their productions. Therefore, since speaker variability is an intrinsic feature of individuals with Down syndrome, it should be considered to attain an effective automatic prosodic assessment system.
AB - © 2019 by the authors. Prosody is a fundamental speech element responsible for communicative functions such as intonation, accent and phrasing, and prosodic impairments of individuals with intellectual disabilities reduce their communication skills. Yet, technological resources have paid little attention to prosody. This study aims to develop an automatic classifier to predict the prosodic quality of utterances produced by individuals with Down syndrome, and to analyse how inter-individual heterogeneity affects assessment results. A therapist and an expert in prosody judged the prosodic appropriateness of a corpus of Down syndrome' utterances collected through a video game. The judgments of the expert were used to train an automatic classifier that predicts prosodic quality by using a set of fundamental frequency, duration and intensity features. The classifier accuracy was 79.3% and its true positive rate 89.9%. We analyzed how informative each of the features was for the assessment and studied relationships between participants' developmental level and results: interspeaker variability conditioned the relative weight of prosodic features for automatic classification and participants' developmental level was related to the prosodic quality of their productions. Therefore, since speaker variability is an intrinsic feature of individuals with Down syndrome, it should be considered to attain an effective automatic prosodic assessment system.
KW - ABILITY
KW - ADOLESCENTS
KW - Automatic classification
KW - CHILDREN
KW - Down syndrome
KW - Educational video games
KW - LANGUAGE IMPAIRMENT
KW - Prosody
KW - SPEECH
KW - VOICE
KW - automatic classification
KW - educational video games
KW - prosody
UR - http://www.mendeley.com/research/automatic-assessment-prosodic-quality-down-syndrome-analysis-impact-speaker-heterogeneity
U2 - 10.3390/app9071440
DO - 10.3390/app9071440
M3 - Article
SN - 2076-3417
VL - 9
SP - 1440
EP - 1457
JO - Applied Sciences (Switzerland)
JF - Applied Sciences (Switzerland)
IS - 7
M1 - 1440
ER -