Dublin, April 22, 2022 (GLOBE NEWSWIRE) -- The "Global Emotion Detection and Recognition Market with COVID-19 Analysis, by Component (Software [Facial Expression Recognition, Speech & Voice Recognition], Services), Application Area, End-user, Vertical, and Region - Forecast to 2027" report has been added to ResearchAndMarkets.com's offering.
The global emotion detection and recognition market is projected to grow from USD 23.6 billion in 2022 to USD 43.3 billion by 2027, at a Compound Annual Growth Rate (CAGR) of 12.9% during the forecast period.
The major factors driving the market growth include the rising need for accretion of speech-based emotion detection systems to analyze emotional states, Adoption of IoT, AI, ML, and deep learning technologies across the globe, growing demand in the Automotive AI industry, growing need for high operational excellence, and rising need for socially intelligent artificial agents.
By software, the biosensing solutions and apps segment to hold the largest market size in 2022
Biosensing solutions and apps collect human gestures through sensors, such as Electrocardiography (ECG), Electroencephalography (EEG), Electromyography (EMG), eye tracking sensors, and wearables. These software tools convert the collected inputs into mathematical form and interpret them for various applications, which is used in online learning systems, law enforcement sectors (applications, such as lie-detection and other threat detection), and healthcare.
The use of biosensing software tools and apps to analyze growing inputs from the increasing adoption of biosensors, such as wearables, can act as a game changer for this particular market.
Asia Pacific to register the highest growth rate during the forecast period
Asia Pacific (APAC) has witnessed an advanced and dynamic adoption of new technologies and is expected to record the highest CAGR in the global emotion detection and recognition market during the forecast period. APAC constitutes major economies, such as China, Japan, and Australia, which are expected to register high growth rates in the emotion detection and recognition market.
End-users, such as industrial, commercial, and enterprises are expected to adopt emotion detection and recognition solutions at the highest rate in the region. Companies operating in APAC would benefit from the flexible economic conditions, industrialization-motivated policies of the governments, as well as from the growing digitalization, which is expected to have a significant impact on the business community.
Key Topics Covered:
1 Introduction
2 Research Methodology
3 Executive Summary
4 Premium Insights
4.1 Brief Overview of the Emotion Detection and Recognition Market
4.2 Market Share of Top Three Verticals and Regions, 2022
4.3 Market, by Component, 2022-2027
4.4 Market, by Software, 2022-2027
4.5 Market, by End-user, 2022-2027
4.6 Market Investment Scenario, by Region
5 Market Overview and Industry Trends
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers
5.2.1.1 Accretion of Speech-based Emotion Detection Systems to Analyze Emotional States
5.2.1.2 Adoption of IoT, AI, ML, and Deep Learning Technologies Worldwide to Increase Demand
5.2.1.3 Rising Need for Socially Intelligent Artificial Agents
5.2.2 Restraints
5.2.2.1 High Production Cost of Emotion Detection and Recognition Systems
5.2.2.2 Oligopoly in the Development of the Speech and Voice Recognition Technologies Using Neural Networks Restricting Their Use for Cloud-based Services
5.2.3 Opportunities
5.2.3.1 Increasing Government Initiatives to Leverage Benefits of Emotion Detection and Recognition Technology
5.2.3.2 Growing Demand in the Automotive AI Industry
5.2.3.3 Growing Partnerships and Widening Ecosystems
5.2.4 Challenges
5.2.4.1 Complex Systems for Emotion Recognition
5.2.4.2 Lack of Awareness, Knowledge, and Technical Skills Among It Experts of an Organization
5.2.4.3 Threat of Privacy and Data Breach
5.3 Market Dynamics During the COVID-19 Outbreak
5.3.1 Drivers and Opportunities
5.3.2 Restraints and Challenges
5.4 Use Cases
5.4.1 Affectiva Helped GIPHY to Bring Emotions and Expressions to Digital Communication
5.4.2 Affectiva Helped Peppy Pals to Develop Educational Apps with Social and Emotional Intelligence (SEL/EQ)
5.4.3 IBM Helped NVISO to Build a Cloud Solution That Analyzes Facial Expressions
5.4.4 NEC Helped the Sydney Coliseum Theatre by Providing Venue Solutions, Including Facial Recognition, Display, and Network Infrastructure
5.5 Value Chain
5.6 Market Ecosystem
5.7 Technology Analysis
5.7.1 Emotion Detection and Recognition and AI and ML
5.7.2 Emotion Detection and Recognition and Deep Learning Technology
5.7.3 Emotion Detection and Recognition and In-Cabin Sensing Technology
5.8 Porter's Five Forces Model Analysis
5.9 Key Stakeholders and Buying Criteria
5.9.1 Key Stakeholders in the Buying Process
5.10 Pricing Model Analysis
5.11 Patent Analysis
5.12 Trends/Disruptions Impacting the Customer's Business
5.13 Tariff and Regulatory Landscape
5.14 Key Conferences & Events in 2022-2023
6 Emotion Detection and Recognition Market, by Technology
6.1 Introduction
6.2 Feature Extraction and 3D Modeling
6.2.1 Feature Extraction and 3D Modeling: Market Drivers
6.2.2 Feature Extraction and 3D Modeling: COVID-19 Impact
6.3 Biosensors Technology
6.3.1 Biosensors Technology: Market Drivers
6.3.2 Biosensors Technology: COVID-19 Impact
6.4 Natural Language Processing
6.4.1 Natural Language Processing: Market Drivers
6.4.2 Natural Language Processing: COVID-19 Impact
6.5 Machine Learning
6.5.1 Machine Learning: Market Drivers
6.5.2 Machine Learning: COVID-19 Impact
6.6 Other Technologies
7 Emotion Detection and Recognition Market, by Hardware
7.1 Introduction
7.2 Sensors
7.2.1 Sensors: Market Drivers
7.2.2 Sensors: COVID-19 Market Drivers
7.3 Cameras
7.3.1 Cameras: Market Drivers
7.3.2 Cameras: COVID-19 Impact
7.4 Storage Devices and Processors
7.4.1 Storage Devices and Processors: Market Drivers
7.4.2 Storage Devices and Processors: COVID-19 Market Drivers
7.5 Others
8 Emotion Detection and Recognition Market, by Component
8.1 Introduction
8.2 Software
8.2.1 Software: Emotion Recognition and Recognition Market Drivers
8.2.2 Software: COVID-19 Impact
8.3 Services
8.3.1 Services: Table 17 Services Market Size, by Region, 2016-2021 (USD Million)
8.3.3 Professional Services
8.3.4 Managed Services
9 Emotion Detection and Recognition Market, by Software
9.1 Introduction
9.2 Facial Expression Recognition
9.2.1 Facial Expression Recognition: Market Drivers
9.2.2 Facial Expression Recognition: COVID-19 Impact
9.3 Biosensing Solutions and Apps
9.3.1 Biosensing Solutions and Apps: Market Drivers
9.3.2 Biosensing Solutions and Apps: COVID-19 Impact
9.4 Speech and Voice Recognition
9.4.1 Speech and Voice Recognition: Emotion Detection and Recognition Market Drivers
9.4.2 Speech and Voice Recognition: COVID-19 Impact
9.5 Gesture and Posture Recognition
9.5.1 Gesture and Posture Recognition: Market Drivers
9.5.2 Gesture and Posture Recognition: COVID-19 Impact
10 Emotion Detection and Recognition Market, by Application Area
10.1 Introduction
10.2 Medical Emergency
10.2.1 Medical Emergency: Market Drivers
10.2.2 Medical Emergency: COVID-19 Impact
10.3 Marketing and Advertising
10.3.1 Marketing and Advertising: Market Drivers
10.3.2 Marketing and Advertising: COVID-19 Impact
10.4 Law Enforcement, Surveillance, and Monitoring
10.4.1 Law Enforcement, Surveillance, and Monitoring: Emotion Detection and Recognition Market Drivers
10.4.2 Law Enforcement, Surveillance, and Monitoring: COVID-19 Impact
10.5 Entertainment and Consumer Electronics
10.5.1 Entertainment and Consumer Electronics: Market Drivers
10.6 Other Application Areas
11 Emotion Detection and Recognition Market, by End-user
11.1 Introduction
11.2 Enterprises
11.2.1 Enterprises: Market Drivers
11.2.2 Enterprises: COVID-19 Market Drivers
11.3 Defense and Security Agency
11.3.1 Defense and Security Agency: Market Drivers
11.3.2 Defense and Security Agency: COVID-19 Impact
11.4 Commercial
11.4.1 Commercial: Emotion Detection and Recognition Market Drivers
11.4.2 Commercial: COVID-19 Impact
11.5 Industrial
11.5.1 Industrial: Market Drivers
11.5.2 Industrial: COVID-19 Impact
11.6 Other End-users
12 Emotion Detection and Recognition Market, by Vertical
12.1 Introduction
12.2 Academia and Research
12.2.1 Academia and Research: Market Drivers
12.2.2 Academia and Research: COVID-19 Impact
12.3 Media and Entertainment
12.3.1 Media and Entertainment: Market Drivers
12.3.2 Media and Entertainment: COVID-19 Impact
12.4 IT and ITeS
12.4.1 IT and ITeS: Emotion Detection and Recognition Market Drivers
12.4.2 IT and ITeS: COVID-19 Impact
12.5 Healthcare and Social Assistance
12.5.1 Healthcare and Social Assistance: Market Drivers
12.5.2 Healthcare and Social Assistance: COVID-19 Impact
12.6 Telecommunications
12.6.1 Telecommunications: Emotion Detection and Recognition Market Drivers
12.6.2 Telecommunications: COVID-19 Impact
12.7 Retail and e-Commerce
12.7.1 Retail and e-Commerce: Market Drivers
12.7.2 Retail and e-Commerce: COVID-19 Impact
12.8 Automotive
12.8.1 Automotive: Market Drivers
12.8.2 Automotive: COVID-19 Impact
12.9 Banking, Financial Services, and Insurance
12.9.1 Banking, Financial Services, and Insurance: Emotion Detection and Recognition Market Drivers
12.9.2 Banking, Financial Services, and Insurance: COVID-19 Impact
12.10 Other Verticals
13 Emotion Detection and Recognition Market, by Region
14 Competitive Landscape
14.1 Overview
14.2 Market Evaluation Framework
14.3 Revenue Analysis of Leading Players
14.4 Market Share Analysis of the Top Market Players
14.5 Historical Revenue Analysis
14.6 Ranking of Key Players in the Market
14.7 Key Company Evaluation Quadrant
14.7.1 Stars
14.7.2 Emerging Leaders
14.7.3 Pervasive Players
14.7.4 Participants
14.8 Competitive Benchmarking
14.8.1 Key Company Evaluation Quadrant
14.8.2 SME/Startup Company Evaluation Quadrant
14.9 SME/Startup Evaluation Quadrant
14.9.1 Progressive Companies
14.9.2 Responsive Companies
14.9.3 Dynamic Companies
14.9.4 Starting Blocks
14.10 Competitive Scenario and Trends
14.10.1 New Product Launches and Product Enhancements
14.10.2 Deals
15 Company Profiles
15.1 Key Players
15.1.1 NEC
15.1.2 IBM
15.1.3 Microsoft
15.1.4 Apple
15.1.5 Google
15.1.6 Tobii
15.1.7 Affectiva
15.1.8 Elliptic Labs
15.1.9 Intel
15.1.10 Cognitec
15.1.11 NVISO
15.1.12 Noldus
15.2 Other Players
15.2.1 Gesturetek
15.2.2 iMotions
15.2.3 Numenta
15.2.4 PointGrab
15.2.5 Ayonix
15.2.6 Pyreos
15.2.7 Eyeris
15.2.8 Beyond Verbal
15.2.9 Kairos
15.2.10 Sentiance
15.2.11 Sightcorp
15.2.12 CrowdEmotion
15.2.13 Sony Depthsensing Solutions
16 Adjacent Markets
17 Appendix
For more information about this report visit https://www.researchandmarkets.com/r/xwnl51
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