This technology offer is a healthcare-grade emotion recognition AI with close to 10 years of R&D and commercial use that can discern emotions, high accuracy, and is capable of extracting concealed feelings. The strength of the algorithm arises from the volume and granularity of data collected, enabling the AI engine to detect and assess a broad range of emotions with precision. There are annotated datasets from various fields of psychology; after extensive training and validation, the algorithm recognises the minutiae scale of emotions for applications across platforms. This technology offer can be used in mental health analysis, vehicle safety, education, unbiased emotion feedback for advertising and public security. It has been deployed for audience emotion measurement, customer satisfaction, human resources and training applications, etc.
The technology owner is keen to out-license this technology and/or work with technology collaborators who can further co-develop this technology. E.g., companies with relevant hardware, and require lightweight emotion recognition AI at the edge to bring new products/services into the market, such as non-intrusive emotion recognition cameras in shopping malls.
The features and specifications of this emotion recognition AI include:
- Using psychology circumplex model with 2 dimensions for subtle expressions analysis
- Real-time processing and analysis for emotional states of individuals and large groups
- The algorithm accounts for ethnicity and cultural differences with high accuracy especially in negative expressions
- Thousands of mood detection with accuracy of 93%
- Deployment methods include: Apps, SDK, Raspberry Pi, Cloud Service
There are various annotated datasets:
- Cognitive, experimental and social psychology fields are used to train our algorithm to detect emotions of drivers and large groups - on safety, interactive infotainment or malicious intent
- Clinical, counselling and psychological fields are used to train the algorithm to recognize emotions that can be used to aid detection and intervention of mental health.
- Behavioural, educational, and human factors psychology fields are used to train the algorithm to detect attention and engagement levels of participants/users in education and advertising research.
- Cross-cultural, developmental, social and forensic psychology fields are used to train the algorithm to detect emotions of people in crowded places for public safety and experience
The potential applications of the emotion recognition AI include:
- Real-time emotion detection for mental health, elderly care via remote telehealth platforms and emotional support health companion devices
- Adaptive learning content, curriculum developed with emotion data and mood-meter for classrooms or exhibitions
- Objective aptitude training with enlarged behavioral cues on situational training, online training and cognition skill development
- Online recruitment psychometric evaluation with candidate emotion analysis
- Emotion insights into A/B testing/ packaging / POS satisfaction survey or guest services concierge measurement
- Unbiased genuine emotion feedback for focus group or market research analytics
- Gather emotion data at any displays and make improvements or create more interactive contents
Benefits of this technology offer include the following:
- Gain emotion insights non-intrusively for content, A/B testing and packaging
- Boost content designed in a practical approach beyond spoken or written feedback (emotion feedback is more genuine)
- Enhance survey measurement (high survey scores but low emotion recognition, as users tend to be polite when giving feedback)
- Strengthen market research methods to formulate preferences based on emotions in response to new services or products
- Deepen behavioral methods and automate emotion analysis to scale data collection efforts from multiple sources.
- Discover emotions in real-time for customers service, improve productivity, save costs and make user experience
- Quantify consumer behavior trends - optimise everything from shelf-level displays to store layout based on customers’ emotion analytics
- Link emotion analytics data on multiple IoT devices, to have broad understanding of user behaviors
- Extend emotion detection for better measurement in interviews, employee morale and HR tools on recruiting strategies
- Humanise computer interactions in intelligent personal assistant, concierge service and customer service
- Infuse emotion intelligence into devices making them truly social, empathic and smarter
- Expand DOOH marketing measurement in public places, in transit, commercial, retail venue, billboards, street and roads
- Widen emotional analysis at point of experience for a greater understanding of behavior patterns to help predict likely future purchasing
- Insight into what impacts customer emotions to help drive sales, improve product and service offerings and experiences