Top 7 ML-powered emotion recognition tools

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The research on emotions goes one step further: it interprets your enthusiastic state based on your health information. It’s one of a growing number of apps that claim to use emotion AI or emotional processing to measure your sentiments.

The field attempts to understand an individual’s sentiments by utilizing various data sources, including appearances and occasionally used for business objectives.

Here is a list of recent machine learning-powered emotion recognition solutions:

Twiggle:

Twiggle is an innovative company that uses machine learning and natural language processing to provide location-based scanning answers for online business locations. The Semantic API allows online retailers to expand their existing search capabilities by incorporating semantic understanding into their current search engine.

The North Face:

The North Face is one of the leading e-commerce shop websites, providing users wanting to purchase things from their sites with a comprehensive approach. The North Face is well-known for using IBM Watson’s machine learning capabilities to engage with its customers electronically.

Google Now:

Google Now is connected to Google Feed; it functions as a virtual assistant, doing all of the customers’ significant activities and exercises. It integrates with natural language processing, which deciphers the client’s voice requests and acts appropriately.

Amazon Alexa:

Amazon Alexa is a virtual assistant with voice and sentiment recognition capabilities. Alexa offers neural networks, a unique machine learning concept. When used, it produces the same organic feelings as human brain systems. Alexa also exhibits several characteristics of sentiment analysis. The majority of its sentiment analysis relies on voice recognition algorithms.

Akinator:

Akinator is both a web-based game and a mobile application.  It tries to figure out which fictitious or real-life “character” would ask a series of 12 questions during playing. It integrates artificial intelligence technologies, which design the questions such that the difficulty level increases in direct proportion to the user’s efforts and level of experience. The Akinator is well-known for its incredibly accurate questioning technique. This questionnaire yields a precise response.

EmoVu:

EmoVu face recognition products, created by Eyeris, combine artificial intelligence with micro demeanour discovery to enable an office to “precisely evaluate their substance’s passionate dedication and viability on their ideal interest group.” EmoVu provides broad stage support, including various components such as head position, slant, eye following, eye open/close, and that’s just the beginning, with a Desktop SDK, Mobile SDK, and an API for fine-grained management. 

Nviso:

Nviso, founded in Switzerland, specializes in emotion video analytics, employing 3D face imaging technology to track various facial data points to generate likelihoods for seven distinct emotions. Nviso promises to provide a real-time image API, yet there is no free demo available. They have a reputation, having won an IBM award for intelligent computing in 2013. Nviso may not be the best choice for a developer seeking a rapid plug-and-play solution with immediate assistance due to its worldwide corporate attitude.

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