4 citations · 10 across the 11 of their papers we have counts for
5 papers · 1 filter
Evaluation of Speech Foundation Models for ASR on Child-Adult Conversations in Autism Diagnostic Sessions
Aditya Ashvin, Rimita Lahiri, Aditya Kommineni +4
Reliable transcription of child-adult conversations in clinical settings is crucial for diagnosing developmental disorders like Autism. Recent advances in deep learning and availab…
Robust Self Supervised Speech Embeddings for Child-Adult Classification in Interactions involving Children with Autism
Rimita Lahiri, Tiantian Feng, Rajat Hebbar +3
We address the problem of detecting who spoke when in child-inclusive spoken interactions i.e., automatic child-adult speaker classification. Interactions involving children are ri…
Understanding Spoken Language Development of Children with ASD Using Pre-trained Speech Embeddings
Anfeng Xu, Rajat Hebbar, Rimita Lahiri +5
Speech processing techniques are useful for analyzing speech and language development in children with Autism Spectrum Disorder (ASD), who are often varied and delayed in acquiring…
A Context-Aware Computational Approach for Measuring Vocal Entrainment in Dyadic Conversations
Rimita Lahiri, Md Nasir, Catherine Lord +2
Vocal entrainment is a social adaptation mechanism in human interaction, knowledge of which can offer useful insights to an individual's cognitive-behavioral characteristics. We pr…
Learning Domain Invariant Representations for Child-Adult Classification from Speech
Rimita Lahiri, Manoj Kumar, Somer Bishop +1
Diagnostic procedures for ASD (autism spectrum disorder) involve semi-naturalistic interactions between the child and a clinician. Computational methods to analyze these sessions r…