An important part of the human-computer interaction process is speech emotion recognition (SER), which has been receiving more attention in recent years. However, although a wide diversity of methods ...

There has been a lot of previous works on speech emotion with machine learning method. However, most of them rely on the effectiveness of labelled speech data. In this paper, we propose a novel ...

Zheng (2017) presented an EEG emotion recognition algorithm based on group sparse canonical correlation analysis (GSCCA), which can improve the accuracy of emotion recognition. In Xing et al. (2019) , ...

A vector quantized masked autoencoder for speech emotion recognition Samir Sadok, Simon Leglaive, Renaud Séguier IEEE ICASSP 2023 Workshop on Self-Supervision in Audio, Speech and Beyond (SASB). If ...

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 ...

The growing use of emotion recognition AI is causing alarm among ethicists. They warn that the tech is prone to racial biases, doesn’t account for cultural differences, and is used for mass ...

Jan 27 (Thomson Reuters Foundation) - Technology that measures emotions based on biometric indicators such as facial movements, tone of voice or body movements, is increasingly being marketed in ...

A Chinese AI emotion-recognition system can monitor facial features to track how they feel. Don't even think about faking a smile. The system is able to analyze if the emotion displayed is genuine.

Emotion recognition technology typically relies on software to look at any number of qualities — facial expressions, tone of voice or word choice — to automatically detect emotional state.

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.