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PUBLISHER: Knowledge Sourcing Intelligence | PRODUCT CODE: 1279627

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PUBLISHER: Knowledge Sourcing Intelligence | PRODUCT CODE: 1279627

Emotion Detection and Recognition Market - Forecasts from 2023 to 2028

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The emotion detection and recognition market is expected to grow at a CAGR of 11.71% from a market size of US$17.48 billion in 2021 to reach US$37.938 billion in 2028. Emotion detection and recognition refers to the process of integrating different computer technologies including machine learning algorithms, artificial intelligence software, natural language processing, and biosensor systems to detect and recognize human emotions by analyzing their face, gestures, and voice. It examines facial movements, analyzes voice modulation, and identifies body gestures to provide insight into the emotional state of the user. The technological advancements in AI technology have resulted in a relative increase in the accuracy of emotion detection software which is resulting in higher consumption of emotion recognition software. This software allows companies to understand the preferences of their users. The ability to receive emotional feedback can help companies to enhance their products. Therefore, it can be expected that the emotion detection and recognition market will witness significant growth over the forecast period.

The rise in online marketing strategies have resulted in a higher demand for the emotion detection and recognition market.

According to a report published by Sprout Social Company, approximately 93% of companies have expanded their customer base by gaining new customers through social media video advertisements. As a result, advertising agencies and marketing companies are considering the adoption of emotion detection and recognition software to analyze the effectiveness of their content and examine consumers' behavior for future reference. The employment of emotion recognition software could aid companies in thoroughly investigating the different components of their advertisements and correlating them with the emotions of the viewers. Therefore, the growth of digital marketing is driving the demand for emotion recognition and detection software.

The ethical issues associated with the use of emotion detection software could limit the expansion of the emotion detection and recognition market.

The ethical issues of privacy violation as a result of the implementation of the emotion detection and recognition market are causing a backlash among several consumers. Research conducted by the National Institute of Standards and Technology in the US revealed that approximately 50% of adult faces in the country have been recorded in the facial recognition software database. Consequentially, an increasing number of customers are concerned about the invasion of their private space by emotion and facial detection software. For instance, the state of Washington has introduced a new bill to prohibit the use of facial and biometric recognition software in its government departments and agencies. As a result of the negative sentiment among the public, companies have restrained the use of emotional AI. For example, Microsoft withdrew the application of emotion detection software from its cloud-based solutions in 2022. Therefore, this could potentially limit the development of the emotion detection and recognition market.

Key Developments

  • In July 2022, Lightbulb Ai, an emotional AI startup in India secured an additional investment of US$1.5 million to expand its datasets and strengthen its machine learning algorithms. This startup has four clients including a Columbian company and is planning on using the investment to expand its operations to cater to the international market.
  • In May 2021, Smart Eye, a Swedish company producing software services to track eye movements acquired Affectiva, a US company specializing in the production of emotion recognition software, for US$73.5 million to diversify their vehicle interior sensing capabilities.
  • In January 2021, Herta Security launched a new emotion detection software BioObserver by collaborating with its clients in the law execution department to analyze videos and identify emotions based on the micro-movements in the facial biometrics including orientation of the head and the direction of the gaze of a person.

The implementation of emotional AI and other emotion detection software in schools and classrooms provides an opportunity to examine the class atmosphere and the emotional state of the children.

For instance, Find Solutions AI has collaborated with schools in Hong Kong to interpret the negative and positive changes in the emotions of school children by analyzing their facial muscle movements. This can assist the teachers and school faculty to gain a better understanding of the student's concentration ability and the effectiveness of their teaching. The increasing complexity of school curriculum and high competition levels among students has resulted in an increase in the number of mental health issues and suicide incidents. For instance, the National Crime Records Bureau of India revealed that suicide incidents among students increased by approximately 4.5% in 2022 in comparison with its previous year's records. Therefore, the application of emotion detection software could enable educational institutions to analyze micro-movements in students to analyze their emotional and psychological well-being. Hence, the increasing requirement for good emotional and psychological health in the education sector propels the growth of the emotion detection and recognition market.

North America holds a prominent share of the emotion detection and recognition market and is expected to grow significantly over the forecasted period.

The presence of a strong AI technology market and the rapid advancements in computer software are stimulating the application of the emotion detection and recognition market across different industries including the automotive and retail sectors in North America. In addition, leading technology companies in North America like Google, IBM, Microsoft, and Apple are actively investing to innovate new developments in artificial intelligence software in all fields including emotional AI, and are constantly striving to improve their product portfolio to offer better services to their customers. In an attempt to improve the user experience, these companies have been implementing artificial intelligence software in conversational chatbots and emotion detection solutions. Further, the emergence of new AI-tech startups in Canada and the US specializing in the creation of emotion recognition software such as Wearehuman.io, Braiq, Nuralogix, Cynny, and Mad Street Den provides an opportunity for the development of emotion detection software in the region. Hence, it can be anticipated that the emotion detection and recognition market will gradually grow over the forecast period.

Market Segmentation

By Type

  • Facial Recognition
  • Gesture Recognition
  • Speech Recognition

By Technology

  • Biosensors
  • Natural Language Processing
  • Machine Learning

By Application

  • Gaming
  • Virtual Assistants
  • Surveillance
  • Recruitment
  • Others

By End-Users

  • Automotive
  • Consumer Electronics
  • Government
  • Healthcare
  • Education
  • Others

By Geography

  • North America
    • USA
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Others
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Others
  • Middle East and Africa
    • Saudi Arabia
    • UAE
    • Others
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Singapore
    • Indonesia
    • Others
Product Code: KSI061614872



  • 1.1. Market Overview
  • 1.2. Market Definition
  • 1.3. Scope of the Study
  • 1.4. Market Segmentation
  • 1.5. Currency
  • 1.6. Assumptions
  • 1.7. Base, and Forecast Years Timeline


  • 2.1. Research Data
  • 2.2. Research Design


  • 3.1. Research Highlights


  • 4.1. Market Drivers
  • 4.2. Market Restraints
  • 4.3. Porter's Five Forces Analysis
    • 4.3.1. Bargaining Power of Suppliers
    • 4.3.2. Bargaining Power of Buyers
    • 4.3.3. Threat of New Entrants
    • 4.3.4. Threat of Substitutes
    • 4.3.5. Competitive Rivalry in the Industry
  • 4.4. Industry Value Chain Analysis


  • 5.1. Introduction
  • 5.2. Facial Recognition
  • 5.3. Gesture Recognition
  • 5.4. Speech Recognition


  • 6.1. Introduction
  • 6.2. Biosensors
  • 6.3. Natural Language Processing
  • 6.4. Machine Learning


  • 7.1. Introduction
  • 7.2. Gaming
  • 7.3. Virtual Assistants
  • 7.4. Surveillance
  • 7.5. Recruitment
  • 7.6. Others


  • 8.1. Introduction
  • 8.2. Automotive
  • 8.3. Consumer Electronics
  • 8.4. Government
  • 8.5. Healthcare
  • 8.6. Education
  • 8.7. Others


  • 9.1. Introduction
  • 9.2. North America
    • 9.2.1. USA
    • 9.2.2. Canada
    • 9.2.3. Mexico
  • 9.3. South America
    • 9.3.1. Brazil
    • 9.3.2. Argentina
    • 9.3.3. Others
  • 9.4. Europe
    • 9.4.1. United Kingdom
    • 9.4.2. Germany
    • 9.4.3. France
    • 9.4.4. Italy
    • 9.4.5. Spain
    • 9.4.6. Others
  • 9.5. Middle East and Africa
    • 9.5.1. Saudi Arabia
    • 9.5.2. UAE
    • 9.5.3. Others
  • 9.6. Asia Pacific
    • 9.6.1. China
    • 9.6.2. Japan
    • 9.6.3. India
    • 9.6.4. South Korea
    • 9.6.5. Australia
    • 9.6.6. Singapore
    • 9.6.7. Indonesia
    • 9.6.8. Others


  • 10.1. Major Players and Strategy Analysis
  • 10.2. Emerging Players and Market Lucrativeness
  • 10.3. Mergers, Acquisitions, Agreements, and Collaborations
  • 10.4. Vendor Competitiveness Matrix


  • 11.1. Affective
  • 11.2. Apple Inc.
  • 11.3. Microsoft Corporation
  • 11.4. Eyeris Technology Inc.
  • 11.5. Noldus Information Technology BV
  • 11.6. MorphCast
  • 11.7. AritaWeb
  • 11.8. audEERING GmbH
  • 11.9. NVISO SA
  • 11.10. Paravision
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Jeroen Van Heghe

Manager - EMEA



Christine Sirois

Manager - Americas


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