Future Timeline

The rapid advancement of natural language processing (NLP) models and large language models (LLMs) has enabled the development of new use-specific conversational agents designed to answer specific types of queries. These range from AI agents that offer academic support to platforms offering general financial, legal or medical advice.

Researchers at Hefei University of Technology and Hefei Comprehensive National Science Center recently worked to develop an AI-based platform that can provide non-professional, but potentially helpful, psychological support. Their paper, presented at the International Conference on Multimedia Modeling held in Amsterdam from Jan. 29 to Feb. 2, introduces EmoAda, a conversational system trained to engage in emotional conversations, offering low-cost and basic psychological support.

"Our paper originated from a concern over the increasing prevalence of psychological disorders such as depression and anxiety, particularly following the COVID-19 pandemic, as well as the significant gap in the availability of professional psychological services," Xiao Sun, co-author of the paper, told Tech Xplore.

"This work builds on various research efforts, such as those by Fei-Fei Li et al on measuring depression severity from spoken language and facial expressions, those by Xiao Sun et al on multimodal attention networks for personality assessment, and the development of AI-based emotional support systems, like Google's LaMDA and OpenAI's ChatGPT."

The primary objective of this recent study was to create a cost-effective psychological support system that could perceive the emotions of users based on different inputs, producing personalized and insightful responses. This system is not designed to substitute professional help, but rather to alleviate stress and assist users in increasing their mental flexibility, a feature that has been associated with good mental health.

"EmoAda is a multimodal emotion interaction and psychological adaptation system designed to offer psychological support to individuals with limited access to mental health services," Sun explained. "It works by collecting real-time multimodal data (audio, video, and text) from users, extracting emotional features, and using a multimodal large language model to analyze these features for real-time emotion recognition, psychological profiling, and guidance strategy planning."

spryfusion wrote: ↑Sun Mar 03, 2024 5:18 am

firestar464 wrote: ↑Tue Mar 05, 2024 8:10 am

pov: you are still waiting for that invite from Stable Diffusion