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pro vyhledávání: '"Dong, Zhongren"'
Autor:
Zhang, Zixing, Xu, Weixiang, Dong, Zhongren, Wang, Kanglin, Wu, Yimeng, Peng, Jing, Wang, Runming, Huang, Dong-Yan
Computational paralinguistics (ComParal) aims to develop algorithms and models to automatically detect, analyze, and interpret non-verbal information from speech communication, e. g., emotion, health state, age, and gender. Despite its rapid progress
Externí odkaz:
http://arxiv.org/abs/2411.09349
With the increasing implementation of machine learning models on edge or Internet-of-Things (IoT) devices, deploying advanced models on resource-constrained IoT devices remains challenging. Transformer models, a currently dominant neural architecture
Externí odkaz:
http://arxiv.org/abs/2411.09339
Publikováno v:
publised at ICASSP 2024
Automatically detecting Alzheimer's Disease (AD) from spontaneous speech plays an important role in its early diagnosis. Recent approaches highly rely on the Transformer architectures due to its efficiency in modelling long-range context dependencies
Externí odkaz:
http://arxiv.org/abs/2405.03952
Publikováno v:
In Computer Methods and Programs in Biomedicine October 2021 210
Publikováno v:
In Biomedical Signal Processing and Control September 2021 70
Akademický článek
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