All posts by Artificial Intelligence News -- ScienceDaily

A new way to teach artificial intelligence (AI) to understand human line drawings -- even from non-artists -- has been developed.

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. 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.

Researchers have developed a technique that allows artificial intelligence (AI) programs to better map three-dimensional spaces using two-dimensional images captured by multiple cameras. Because the technique works effectively with limited computational resources, it holds promise for improving the navigation of autonomous vehicles.

An artificial intelligence-powered virtual teammate with a female voice boosts participation and productivity among women on teams dominated by men, according to new research.

Have you ever wished you could understand what your dog is trying to say to you? Researchers are exploring the possibilities of AI, developing tools that can identify whether a dog's bark conveys playfulness or aggression.

A team of researchers have developed a new machine-learning method that detects hate speech on social media platforms with 88 per cent accuracy, saving employees from hundreds of hours of emotionally damaging work.

Cultivating creativity in schools is vital for a future driven by artificial intelligence (AI). But while teachers embrace creativity as an essential 21st century skill, a lack of valid and reliable creativity tests means schools struggle to assess student achievement. Now, a new machine-learning model is providing teachers with access to high-quality, fit-for-purpose creativity tests, that can score assessments in a fraction of the time and a fraction of the cost.

Artificial intelligence (AI) combined with a novel bio-inspired camera achieves 100 times faster detection of pedestrians and obstacles than current automotive cameras. This important step for computer vision and AI and can greatly improve the safety of automotive systems and self-driving cars.

Researchers developed a computer vision framework for posture estimation and identity tracking which they can use in indoor environments as well as in the wild. They have thus taken an important step towards markerless tracking of animals in the wild using computer vision and machine learning.

Engineers have developed an artificial intelligence system that lets someone wearing headphones look at a person speaking for three to five seconds to 'enroll' them. The system then plays just the enrolled speaker's voice in real time, even as the pair move around in noisy environments.

Large language model-based chatbots can't effectively recognize users' motivation when they are hesitant about making healthy behavior changes, but they can support those who are committed to take action, say researchers.

Sarcasm is notoriously tricky to convey through text, and the subtle changes in tone that convey sarcasm often confuse computer algorithms as well, limiting virtual assistants and content analysis tools. So researchers have now developed a multimodal algorithm for improved sarcasm detection that examines multiple aspects of audio recordings for increased accuracy. They used two complementary approaches -- sentiment analysis using text and emotion recognition using audio -- for a more complete picture.

Actually, sometimes consumers don't want to talk to a real person when they're shopping online, a new study suggests. In fact, what they really want is a chatbot that makes it clear that it is not human at all. In a new study, researchers found that people preferred interacting with chatbots when they felt embarrassed about what they were buying online -- items like antidiarrheal medicine or, for some people, skin care products.

Conversational agents (CAs) such as Alexa and Siri are designed to answer questions, offer suggestions -- and even display empathy. However, new research finds they do poorly compared to humans when interpreting and exploring a user's experience.

One group commonly misunderstood by voice technology are individuals who speak African American English, or AAE. Researchers designed an experiment to test how AAE speakers adapt their speech when imagining talking to a voice assistant, compared to talking to a friend, family member, or stranger. The study tested familiar human, unfamiliar human, and voice assistant-directed speech conditions by comparing speech rate and pitch variation. Analysis of the recordings showed that the speakers exhibited two consistent adjustments when they were talking to voice technology compared to talking to another person: a slower rate of speech with less pitch variation.