Emotion Detection and Recognition Market – Overview
As technology develops at a rapid pace, the advances being made are breaking new frontiers on a daily basis. Market Research Future, a firm which specializes in market reports related to the information and communication technology sector among others, recently published a report on this market. The global emotion detection and recognition market is anticipated to grow to approximately USD 65 Billion by 2023, while expanding at a 39% CAGR rate between 2017 and 2023.
Many industry leaders who are extremely well placed in the sector have already begun to invest significantly in the sector. The major focus of these developments are on research and development and expansion by way of mergers and acquisitions. The future growth potential is one of the main motivating factors that is driving the demand for this sector at an exceptionally high rate. Development of wearable technology is one the key motivators for this market’s demand rise.
Global Competitive Analysis
A trend of robust growth has been observed in the market with the addition of new and advanced products, with viability of a business in the industry being a key focus topic. Companies are capturing & solidifying their share of the market segment, by experimenting with various advantage points. As the sector is in a phase of rapid growth, the best long-term growth opportunities for this sector can be captured by ensuring ongoing process improvements and financial flexibility to invest in the optimal strategies. The prominent players in emotion detection and recognition market are – Affectiva (U.S.), Emotient, An Apple Company (U.S.), Eyeris (U.S.), Kairos Ar. Inc. (U.S.), Noldus (Netherlands), nViso. (Switzerland), Realeyes (U.K.).
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Many companies are showing a rise of interest in our emotional lives, encompassing any situation where it might be useful for a machine to know how a person feels. Many retail outlets are significantly interested in tapping this market to influence consumer purchase decisions.
Industry Segments
Emotion detection and recognition market can be segmented on the basis of following:
By Technology the segment comprises of bio sensors technology, pattern recognition, natural language processing (NLP), machine learning, feature extraction and 3d modelling among others. On the basis of software tools, speech and voice recognition, facial expression recognition, bio sensing software tools and apps are the main categories. With the category of service, storage and maintenance, consulting and integration are the main segments. Law enforcement, surveillance and monitoring, marketing & advertising, media & entertainment among others are the areas where this segment has it’s applications. Lastly, the Emotion Detection and Recognition Market’s end users are industrial, commercial, defense, enterprises and security agency, others.
The bio sensor technology is estimated to mature at the highest CAGR rate in the forecast period due to incorporation of several technologies like ECG, EEG, EMG, fMRI, GSR, eye tracking and wearable technology. Wearable bio sensors also have gained much popularity owing to its increasing number of applications especially in military, defense and healthcare.
Detailed Regional Analysis
The regional analysis of emotion detection and recognition market includes regions such as Asia Pacific, North America, Europe and Rest of the World. It has been witnessed that North America is likely to account for the largest share of the market, whereas Asia-Pacific is estimated to grow at the fastest rate during the forecast period. The major growth in emotion detection and recognition market in North America can be attributed to the technical advancements and well established infrastructures in that region.
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Latest Industry News:
Feb 2017 A team at the Massachusetts Institute of Technology built a wearable app that can parse conversation to identify the emotion behind each part of the story. The app, built into a fitness tracker for this research, collects physical and speech data to analyze the overall tone of the story in real time. Using artificial intelligence, the app can also figure out which part of the conversation was happy or sad, and tracks emotional changes in five-second intervals.
Dec 2017 Amazon’s Alexa team is beginning to analyze the sound of users’ voices to recognize their mood or emotional state. This could let Amazon personalize and improve customer experiences, lead to lengthier conversations with the AI assistant, and even open the door to Alexa one day responding to queries based on your emotional state or scanning voice recordings to diagnose disease.
Oct 2017 iPhone X smartphone has features related to emotion detection that are revolutionary. These features will eventually affect all user-facing technologies in business enterprises, as well as in medicine, government, the military and other fields. Out of the box, this Kinect-like component powers Apple’s Face ID security system, which replaces the fingerprint-centric Touch ID of recent iPhones, including the iPhone 8.
Nov 2017 UST Global, has partnered with UXTesting, a Silicon Valley based startup that focuses on User Experience testing to offer improved end consumer experience to its customers. They have been developing more capabilities to address the typical industry gap of obtaining direct user feedback in a natural setting, and quantifying that data into straightforward, measurable, and actionable results. Their emotion detection technology using artificial intelligence will also enable early validation of user emotions and enhance the end user experience.
July 2017 Applied Recognition’s emotion detection and analysis solution, Ver-ED, is powering the Emotions Insight feature in Lenovo’s new virtual training solution, AirClass, a comprehensive virtual training platform. Emotion Insights estimates engagement by measuring eye state, level of attendee focus, as well as whether the attendee has a positive or negative disposition based on a spectrum of common emotions.
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