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Found 6 papers, 1 papers with code
Computational Charisma -- A Brick by Brick Blueprint for Building Charismatic Artificial Intelligence
We then name exemplary use cases of computational charismatic skills before switching to ethical aspects and concluding this overview and perspective on building charisma-enabled AI.
Self-Supervised Attention Networks and Uncertainty Loss Weighting for Multi-Task Emotion Recognition on Vocal Bursts
Vocal bursts play an important role in communicating affect, making them valuable for improving speech emotion recognition.
Dynamic Restrained Uncertainty Weighting Loss for Multitask Learning of Vocal Expression
We propose a novel Dynamic Restrained Uncertainty Weighting Loss to experimentally handle the problem of balancing the contributions of multiple tasks on the ICML ExVo 2022 Challenge.
Continuous-Time Audiovisual Fusion with Recurrence vs. Attention for In-The-Wild Affect Recognition
To clearly understand the performance differences between recurrent and attention models in audiovisual affect recognition, we present a comprehensive evaluation of fusion models based on LSTM-RNNs, self-attention and cross-modal attention, trained for valence and arousal estimation.
Domain Adaptation with Joint Learning for Generic, Optical Car Part Recognition and Detection Systems (Go-CaRD)
Systems for the automatic recognition and detection of automotive parts are crucial in several emerging research areas in the development of intelligent vehicles.
A Novel Fusion of Attention and Sequence to Sequence Autoencoders to Predict Sleepiness From Speech
On the development partition of the data, we achieve Spearman's correlation coefficients of . 324, . 283, and . 320 with the targets on the Karolinska Sleepiness Scale by utilising attention and non-attention autoencoders, and the fusion of both autoencoders' representations, respectively.
