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Found 6 papers, 0 papers with code
Robust Self Supervised Speech Embeddings for Child-Adult Classification in Interactions involving Children with Autism
We address the problem of detecting who spoke when in child-inclusive spoken interactions i. e., automatic child-adult speaker classification.
Understanding Spoken Language Development of Children with ASD Using Pre-trained Speech Embeddings
This paper proposes applications of speech processing technologies in support of automated assessment of children's spoken language development by classification between child and adult speech and between speech and nonverbal vocalization in NLS, with respective F1 macro scores of 82. 6% and 67. 8%, underscoring the potential for accurate and scalable tools for ASD research and clinical use.
A Context-Aware Computational Approach for Measuring Vocal Entrainment in Dyadic Conversations
Vocal entrainment is a social adaptation mechanism in human interaction, knowledge of which can offer useful insights to an individual's cognitive-behavioral characteristics.
Multilingual Speech Recognition using Knowledge Transfer across Learning Processes
Multilingual end-to-end(E2E) models have shown a great potential in the expansion of the language coverage in the realm of automatic speech recognition(ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Understanding of Emotion Perception from Art
Computational modeling of the emotions evoked by art in humans is a challenging problem because of the subjective and nuanced nature of art and affective signals.
Learning Domain Invariant Representations for Child-Adult Classification from Speech
Diagnostic procedures for ASD (autism spectrum disorder) involve semi-naturalistic interactions between the child and a clinician.
