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Fusing traditionally extracted features with deep learned features from the speech spectrogram for anger and stress detection using convolution neural network
Stress and anger are two negative emotions that affect individuals both mentally and physically; there is a need to tackle them as soon as possible. Automated systems are highly required to monitor mental states and to detect early signs of emotional health issues. In the present work convolutional...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Springer US
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8993039/ https://www.ncbi.nlm.nih.gov/pubmed/35431609 http://dx.doi.org/10.1007/s11042-022-12886-0 |