Semantic-wise guidance for efficient multimodal emotion recognition with missing modalities
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00530-024-01310-2.pdf
Reference40 articles.
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2. Araño, K.A., Orsenigo, C., Soto, M., Vercellis, C.: Multimodal sentiment and emotion recognition in hyperbolic space. Expert Syst. Appl. 184, 115507 (2021). https://doi.org/10.1016/j.eswa.2021.115507
3. Baidari, I., Honnikoll, N.: Accuracy weighted diversity-based online boosting. Expert Syst. Appl. 160, 113723 (2020). https://doi.org/10.1016/j.eswa.2020.113723
4. Busso, C., Bulut, M., Lee, C.-C., Kazemzadeh, A., Mower, E., Kim, S., Chang, J.N., Lee, S., Narayanan, S.S.: IEMOCAP: Interactive emotional dyadic motion capture database. Lang. Resour. Eval. 42(4), 335–359 (2008). https://doi.org/10.1007/s10579-008-9076-6
5. Busso, C., Parthasarathy, S., Burmania, A., AbdelWahab, M., Sadoughi, N., Provost, E.M.: MSP-IMPROV: an acted corpus of dyadic interactions to study emotion perception. IEEE Trans. Affect. Comput. 8(1), 67–80 (2017). https://doi.org/10.1109/TAFFC.2016.2515617
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