Seven Interesting Machine Learning-Based Emotion Recognition Tools
Chatbots are not yet considered “artificial intelligence” because they can only predict a user’s interaction by analyzing large amounts of data. We must cultivate their intelligence. Facial expression recognition and semantic elicitation should be researched to improve the “intelligence” of chatbots.
The science of emotions goes further than that; it infers your level of enthusiasm from data on your health. It is one of the growing apps that claim to passively assess your emotions using artificial intelligence for emotions (emotion AI) or emotional processing. Understanding how people feel is the goal of this domain, which is sometimes used for commercial purposes and uses various data focal lengths (including appearance).
Here are some intriguing machine learning based Android emotion recognition systems.
The north face
The North Face is one of the largest e-commerce sites, offering a comprehensive method of handling customers who wish to purchase items from their destinations. Additionally, The North Face is well known for using IBM’s Watson, a machine learning innovation, to hold electronic conversations with customers.
Twiggle is a leading company that uses machine learning and natural language processing to develop scanning responses for online business sites. With the Semantic API, online merchants can improve their search capabilities by incorporating semantic understanding into their web search engine.
The Amazon Alexa virtual assistant has features like voice recognition and emotion recognition. It provides the user with the same natural feel as the human neurological framework. Most of the evaluation calculation consists of speech recognition techniques.
EmoVu facial recognition products, developed by Eyeris, combine AI with micro-behavioral discovery to enable companies “to accurately gauge the passionate dedication and viability of their content to their target interest group.” With its desktop SDK, mobile SDK and API for precise control, EmoVu provides extensive scene support including various following components such as position of head, tilt, eye tracking, eye opening/closing, and many more.
Nviso, founded in Switzerland, is an industry leader in video emotion analysis. The company uses 3D facial imaging technology to continuously analyze numerous facial data points to predict the probabilities of the seven most common human emotions. Nviso promises a real-time image API, but no demo is available. They are well known in the industry and received an IBM award for “Smarter Computing” in 2013. However, developers looking for a simple plug-and-play experience with fast support can look elsewhere than Nviso, which has a more multinational commercial feel.
Kairos-logo Kairos’ Emotion Analysis API offers a more SaaS approach to the facial recognition market. You send the video and they recognize smiles, amazement, anger, hate and lethargy, making this service adaptable and on-demand. You can try their service for free (no registration required) and have your facial reactions to advertisements from various companies analyzed and mapped. The Unblemished Kairos might be the best option for a creation. The Facial Recognition API, Crowd Analytics SDK, and Reporting API seem to be relatively new additions to the ecosystem and are well documented. In addition, an API for analyzing emotional states has just been released.
Google Now, a product associated with Google Feed, acts as a digital personal assistant by automatically managing the essentials of a user’s daily tasks. Equipped with a natural language processor, it can understand and respond to user voice commands.