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Mutual Correlation Attentive Factors in Dyadic Fusion Networks for Speech Emotion Recognition
Emotion recognition in dyadic communication is challenging because: 1. Extracting informative modality-specific representations requires disparate feature extractor designs due to the heterogenous input data formats. 2. How to effectively and efficiently fuse unimodal features and learn associations...
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| Publicado no: | Proc ACM Int Conf Multimed |
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| Main Authors: | , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7085887/ https://ncbi.nlm.nih.gov/pubmed/32201866 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1145/3343031.3351039 |
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