AI recognizes athletes' emotions | ScienceDaily

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AI recognizes athletes' emotions | ScienceDaily
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Using computer-assisted neural networks, researchers have been able to accurately identify affective states from the body language of tennis players during games. For the first time, they trained a model based on artificial intelligence (AI) with data from actual games.

Using computer-assisted neural networks, researchers have been able to accurately identify affective states from the body language of tennis players during games. For the first time, they trained a model based on artificial intelligence with data from actual games. Their study demonstrates that AI can assess body language and emotions with accuracy similar to that of humans. However, it also points to ethical concerns.

For their study,"Recognizing affective states from the expressive behavior of tennis players using convolutional neural networks," sports sciences, software development and computer science researchers from KIT and the University of Duisburg-Essen developed a special AI model. They used pattern-recognition programs to analyze video of tennis players recorded during actual games."Our model can identify affective states with an accuracy of up to 68.

After being fed with this data, the AI learned to associate the body language signals with different affective reactions and to determine whether a point had been won or lost ."Training in natural contexts is a significant advance for the identification of real emotional states, and it makes predictions possible in real scenarios," said Jekauc.

Darko Jekauc, Diana Burkart, Julian Fritsch, Marc Hesenius, Ole Meyer, Saquib Sarfraz, Rainer Stiefelhagen.With generative artificial intelligence transforming the social interaction landscape in recent years, large language models , which use deep-learning algorithms to train GenAI ...

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