Then, CAE is constructed by combining CNN and stacked autoencoder (SAE) for emotion recognition. Compared with other algorithms, the proposed algorithm makes full use of the characteristics of CNN ...

Abstract: An important part of the human-computer interaction process is speech emotion recognition (SER), which has been receiving ... In this paper, we propose a novel algorithm, an autoencoder with ...

The main reason for the low accuracy of emotion recognition system is how to effectively extract emotion-oriented features. In this paper, we propose a novel autoencoder architecture, two-stream ...

Hence, the states of the latent variables that relate to emotional processing must contribute to building robust recognition models. Specifically, we propose to utilize an unsupervised deep generative ...

In this study we are looking at this task from slightly another angle -- emotions recognition. We design a joint of convolutional and recurrent neural networks with the usage of autoencoder to ...

A promising recent trend is to use either soft clustering ... E.M., and Rufiner, H.L. Speech emotion recognition using a deep autoencoder. San Carlos de Bariloche, Argentina, 2013, 934–939. 8. Darwin, ...

IEEE ICASSP 2023 Workshop on Self-Supervision in Audio, Speech and Beyond (SASB). If you use this code for your research, please cite the above paper.

While the use of emotion recognition AI in schools and other settings has caused concern, founder Viola Lam says it can make the virtual classroom as good as — or better than — the real thing.

There’s little scientific basis to emotion recognition technology, so it should be banned from use in decisions that affect people’s lives, says research institute AI Now in its annual report.