Emotion Detection and Recognition Market Growing at High CAGR by 2021

The emotion detection and recognition market size is estimated to grow from USD 6.72 Billion in 2016 to USD 36.07 Billion by 2021, at a Compound Annual Growth Rate (CAGR) of 39.9%.

(EMAILWIRE.COM, July 17, 2019 ) Several factors such as rising demand for sentiment mapping, especially by the marketing and advertising sector, increasing concerns for security, and growing need for application for support during emergency have bolstered the growth of emotion detection and recognition systems. Verticals such as healthcare, banking, defense, commercial security, and many more have boosted the market.

Browse 81 market data tables and 39 figures spread through 133 pages and in-depth TOC on “Emotion Detection and Recognition Market by Technology (Bio-Sensor, NLP, Machine Learning), Software Tool (Facial Expression, Voice Recognition), Service, Application Area, End User, And Region - Global Forecast to 2021”
https://www.marketsandmarkets.com/Market-Reports/emotion-detection-recognition-market-23376176.html

The North American region contains developed countries that have deep-rooted infrastructures, thus favoring the huge demand in the emotion detection and recognition market. Top contributing countries to the emotion detection and recognition market in North America include the U.S. and Canada. The cause for the dominance of these countries is their well-established economies, which allow investments in new technologies. The emotion detection and recognition market is expected to rise significantly, due to huge governmental investments in security & surveillance infrastructure, increased public awareness, and emergence of enhanced technologies backed by analytics.

The major vendors in the emotion detection and recognition market include:
• Affectiva (U.S.)
• Emotient, an Apple Company (U.S.)
• Eyeris (U.S.)
• Kairos Ar. Inc. (U.S.)
• Noldus (Netherlands)
• nViso. (Switzerland)
• Realeyes (U.K.)

The bio-sensor technology incorporates several technologies including ECG, EEG, EMG, fMRI, GSR, eye tracking, and wearable technology. This technology is fast gaining unprecedented interest among the end users and has shown promising developments, especially in the form of wearable technology. Wearable bio-sensors have become quite popular, especially in applications related to sports, military, and healthcare.

NLP is the backbone of the emotion detection and recognition technology. This is essential for the configuration of emotion detection and recognition, as most of the data available with business organizations is in the form of human language or dark data. Thus, NLP is widely used for text analysis, sentiment analysis, summarization of data, and social media monitoring.

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