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pro vyhledávání: '"LORD, CATHERINE"'
Autor:
Feng, Tiantian, Xu, Anfeng, Lahiri, Rimita, Tager-Flusberg, Helen, Kim, So Hyun, Bishop, Somer, Lord, Catherine, Narayanan, Shrikanth
Large Language Models (LLMs) have shown significant potential in understanding human communication and interaction. However, their performance in the domain of child-inclusive interactions, including in clinical settings, remains less explored. In th
Externí odkaz:
http://arxiv.org/abs/2411.10761
Autor:
Ashvin, Aditya, Lahiri, Rimita, Kommineni, Aditya, Bishop, Somer, Lord, Catherine, Kadiri, Sudarsana Reddy, Narayanan, Shrikanth
The ability to reliably transcribe child-adult conversations in a clinical setting is valuable for diagnosis and understanding of numerous developmental disorders such as Autism Spectrum Disorder. Recent advances in deep learning architectures and av
Externí odkaz:
http://arxiv.org/abs/2409.16135
Autor:
Kommineni, Aditya, Bose, Digbalay, Feng, Tiantian, Kim, So Hyun, Tager-Flusberg, Helen, Bishop, Somer, Lord, Catherine, Kadiri, Sudarsana, Narayanan, Shrikanth
Clinical videos in the context of Autism Spectrum Disorder are often long-form interactions between children and caregivers/clinical professionals, encompassing complex verbal and non-verbal behaviors. Objective analyses of these videos could provide
Externí odkaz:
http://arxiv.org/abs/2409.13606
Automating child speech analysis is crucial for applications such as neurocognitive assessments. Speaker diarization, which identifies ``who spoke when'', is an essential component of the automated analysis. However, publicly available child-adult sp
Externí odkaz:
http://arxiv.org/abs/2409.08881
Autor:
Lahiri, Rimita, Feng, Tiantian, Hebbar, Rajat, Lord, Catherine, Kim, So Hyun, Narayanan, Shrikanth
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 richly heterogeneous due to developmental differences. The presence of n
Externí odkaz:
http://arxiv.org/abs/2307.16398
Autor:
Tafolla, Maira1 (AUTHOR) mtafolla@mednet.ucla.edu, Lord, Catherine1 (AUTHOR) clord@mednet.ucla.edu
Publikováno v:
Brain Sciences (2076-3425). Oct2024, Vol. 14 Issue 10, p1033. 21p.
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 propose a context-aware approach for measuring vocal entrainment in dyad
Externí odkaz:
http://arxiv.org/abs/2211.03279
Publikováno v:
In Psychiatric Clinics of North America December 2024 47(4):753-773
Publikováno v:
In Research in Autism Spectrum Disorders January 2025 119