Bedoya Jaramillo, Stefany
(2017).
Acoustic and prosodic analysis of pre-verbal vocalizations of 18-month old toddlers with autism spectrum disorder.
Mémoire.
Québec, Université du Québec, Institut national de la recherche scientifique, Maîtrise en télécommunications, 110 p.
Résumé
Autism Spectrum Disorder (ASD) covers a wide spectrum of symptoms with the main
ones relating to problems with social communication and interaction. Definite ASD
diagnosis is based on the presence of certain symptoms and their severity levels and,
according to current standards, occurs typically at 36 months of age. Recent statistics
show that about 1 in 68 children are diagnosed with autism and there is a recurrence
rate of 18.7% for the biological siblings of autistic individuals. As such, early detection
is critical, as it may allow for intense therapy to be initiated, thus tapping into a
young brain’s plasticity properties and increasing odds of success. Today, researchers
and clinicians have joined efforts to understand and identify new markers of the disorders,
thus allowing for early diagnosis, ideally around 18 months of age. To this end,
acoustic analysis of toddler vocalizations has emerged as a promising area, even for
pre-verbal children. Prosodic and acoustic disorders have been reported for babble and
speech-like vocalizations. As such, pitch, energy and voice quality related features have
been explored for early ASD diagnosis. In this work, we build upon these findings and
propose the use of wavelet-based and speech modulation spectral features for ASD diagnosis
based not only on speech-like verbalizations, but also on cries, laughs, and other
sounds made by the toddlers. We show that the proposed features are complementary
to existing ones and, on a cohort of forty-three 18-month old toddlers, a support vector
machine classifier was capable of correctly discriminating the ASD group from the
typically-developing toddlers with accuracies above 80%, thus outperforming existing
methods. More importantly, we show that with these new features, vocalizations such
as cries, squeals, whines and shouts showed to be more discriminative than babble and
speech-like vocalizations. It is hoped that these findings will lead to more accurate
early diagnosis of ASD symptoms.
Type de document: |
Thèse
Mémoire
|
Directeur de mémoire/thèse: |
Falk, Tiago H. |
Co-directeurs de mémoire/thèse: |
O’Shaughnessy, Douglas |
Mots-clés libres: |
autism spectrum disorder; diagnosis; prosody; wavelets; speech modulation spectrum |
Centre: |
Centre Énergie Matériaux Télécommunications |
Date de dépôt: |
29 janv. 2018 21:51 |
Dernière modification: |
29 janv. 2018 21:51 |
URI: |
http://espace.inrs.ca/id/eprint/6655 |
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