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pro vyhledávání: '"A. Flusberg"'
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:
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:
Xu, Anfeng, Huang, Kevin, Feng, Tiantian, Shen, Lue, Tager-Flusberg, Helen, Narayanan, Shrikanth
Speech foundation models, trained on vast datasets, have opened unique opportunities in addressing challenging low-resource speech understanding, such as child speech. In this work, we explore the capabilities of speech foundation models on child-adu
Externí odkaz:
http://arxiv.org/abs/2406.07890
Interactions involving children span a wide range of important domains from learning to clinical diagnostic and therapeutic contexts. Automated analyses of such interactions are motivated by the need to seek accurate insights and offer scale and robu
Externí odkaz:
http://arxiv.org/abs/2310.01867
Autor:
Xu, Anfeng, Hebbar, Rajat, Lahiri, Rimita, Feng, Tiantian, Butler, Lindsay, Shen, Lue, Tager-Flusberg, Helen, Narayanan, Shrikanth
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 these skills. Early identification and intervention are crucial, but
Externí odkaz:
http://arxiv.org/abs/2305.14117
Autor:
Mues, Marjolein, Chen, Yanru, Demurie, Ellen, Erdogan, Maide, Schaubroeck, Sarah, Tager-Flusberg, Helen, Roeyers, Herbert
Publikováno v:
In Research in Autism Spectrum Disorders September 2024 117
Publikováno v:
Autism and Developmental Language Impairments, Vol 9 (2024)
Background and aims Nongenerative speech is the rote repetition of words or phrases heard from others or oneself. The most common manifestations of nongenerative speech are immediate and delayed echolalia, which are a well-attested clinical feature a
Externí odkaz:
https://doaj.org/article/36306ad637c74a2c9a7d7dbd35e3c7cc
Publikováno v:
PLoS ONE, Vol 19, Iss 1 (2024)
Externí odkaz:
https://doaj.org/article/a8c3d76f75ec413eb33aaaaf44578cf6
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