1 citations · 3 across the 7 of their papers we have counts for
4 papers · 1 filter
Can Generic LLMs Help Analyze Child-adult Interactions Involving Children with Autism in Clinical Observation?
Tiantian Feng, Anfeng Xu, Rimita Lahiri +5
Large Language Models (LLMs) have shown significant potential in understanding human communication and interaction. However, their performance in the domain of child-inclusive inte…
Towards Child-Inclusive Clinical Video Understanding for Autism Spectrum Disorder
Aditya Kommineni, Digbalay Bose, Tiantian Feng +6
Clinical videos in the context of Autism Spectrum Disorder are often long-form interactions between children and caregivers/clinical professionals, encompassing complex verbal and…
Data Efficient Child-Adult Speaker Diarization with Simulated Conversations
Anfeng Xu, Tiantian Feng, Helen Tager-Flusberg +2
Automating child speech analysis is crucial for applications such as neurocognitive assessments. Speaker diarization, which identifies ``who spoke when'', is an essential component…
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…