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市場調查報告書
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2021583

2034年人工智慧情感辨識市場預測：按類型、組件、部署模式、技術、應用、最終用戶和地區分類的全球分析

AI in Emotion Recognition Market Forecasts to 2034- Global Analysis By Type, Component, Deployment Mode, Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，預計到 2026 年，全球情感識別 AI 市場規模將達到 28.2 億美元，在預測期內將以 22.9% 的複合年成長率成長，到 2034 年將達到 147.71 億美元。

人工智慧在情緒辨識領域的應用，是指利用先進的機器學習、深度學習和情緒運算技術，從臉部表情、語調、生理訊號和文字等各種資料來源中辨識、解讀並回應人類情感。這些系統能夠分析細微的行為徵兆，並即時偵測快樂、憤怒和壓力等情緒狀態。人工智慧驅動的情感識別技術增強了人機交互，在醫療保健、客戶體驗、汽車系統和安全等領域實現了更加個性化和富有同理心的響應，並透過數據驅動的學習模型不斷提高識別準確率。

對人性化的人工智慧的需求日益成長

對人性化的人工智慧日益成長的關注是情感識別人工智慧市場的主要驅動力。各組織機構都在尋求能讓機器理解並回應人類情感的技術，從而改善使用者體驗和參與度。這種需求在客戶服務、醫療保健和汽車應用領域尤其明顯，因為同理心的對話能夠提升最終效果。機器學習和情感運算的進步進一步推動了這一趨勢，實現了即時情感洞察，並在各個行業中促進了更深層的人機連接。

資料隱私和安全問題

資料隱私和安全問題仍然是情感識別人工智慧市場的主要阻礙因素。這些系統依賴面部表情、語音模式和生物識別訊號等敏感個人數據，由此引發了倫理和監管方面的挑戰。嚴格的資料保護法律以及公眾對隱私風險日益增強的意識限制了其廣泛應用。企業被迫投資安全的資料處理、匿名化技術和合規系統，這增加了營運的複雜性和成本，最終減緩了情感識別技術的普及。

在行銷和客戶分析領域應用日益廣泛

情緒辨識人工智慧在行銷和客戶分析領域的應用日益廣泛，蘊藏著巨大的成長機會。企業正利用情緒偵測技術，深入了解消費者的行為、偏好以及對產品和宣傳活動的情緒反應。這有助於制定高度個人化的行銷策略，並提升客戶參與。即時情緒回饋能夠幫助品牌最佳化廣告成效、改善用戶體驗並提高轉換率。在競爭日益激烈的市場環境中，企業正擴大採用這些工具來獲取策略優勢。

高昂的實施和開發成本

高昂的實施和開發成本對情感識別人工智慧市場構成重大威脅。開發準確可靠的系統需要對先進演算法、高品質資料集和專用硬體進行大量投資。與現有系統的整合以及持續的維護進一步加重了財務負擔。由於預算限制，中小企業在採用這些技術方面面臨許多挑戰。此外，為了保持準確性和競爭力，還需要不斷升級，這會增加長期成本。

新冠疫情的影響：

新冠疫情對情緒辨識人工智慧市場產生了複雜的影響。初期，疫情導致投資和應用放緩，但向數位通訊的轉型加速了對情緒識別技術的需求。遠距通訊、遠端醫療和虛擬客戶參與的普及，增加了對無需面對面接觸即可解讀情緒訊號的系統的需求。各組織機構紛紛採用這些解決方案來改善使用者體驗並監測員工健康狀況。疫情過後，市場繼續受益於持續的數位轉型和對人工智慧驅動的互動工具日益成長的依賴。

在預測期內，臉部表情辨識細分市場預計將佔據最大的市場佔有率。

由於臉部表情辨識技術的廣泛應用和技術成熟，預計在預測期內，該領域將佔據最大的市場佔有率。該領域利用先進的電腦視覺和深度學習技術即時分析面部表情。其應用範圍涵蓋安防、零售、醫療保健和汽車等行業，在這些行業中，視覺情緒線索至關重要。高解析度攝影機的日益普及和演算法精度的提升進一步鞏固了其市場主導地位，使其成為各終端用戶領域的首選解決方案。

在預測期內，醫療保健服務提供者細分市場預計將呈現最高的複合年成長率。

在預測期內，由於對以患者為中心的護理和心理健康監測的需求不斷成長，醫療服務提供者領域預計將呈現最高的成長率。情緒識別技術有助於識別患者的心理狀態、壓力水平以及對治療的反應。這些系統能夠增強臨床決策能力，並提高患者參與度，尤其是在遠端醫療和遠距照護環境中。對數位醫療基礎設施的投入增加以及人工智慧的整合正在進一步加速這些技術的應用，使醫療服務提供者領域成為關鍵的成長點。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率，這主要得益於其技術基礎設施和先進人工智慧解決方案的早期應用。主要企業的進駐以及在研發方面的大量投入，都推動了市場成長。此外，對更佳客戶體驗和先進醫療保健解決方案的需求，也促進了人工智慧技術的廣泛應用。有利的政府政策和法律規範進一步刺激了創新，鞏固了北美在情感識別人工智慧市場的主導地位。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率，這主要得益於新興經濟體快速的數位轉型和人工智慧技術的日益普及。智慧城市專案、醫療創新以及對客戶分析投入的增加正在推動市場擴張。中國、日本和印度等國家正積極將情感辨識系統整合到各種應用中。消費者意識的提高和技術能力的提升將進一步加速成長，使亞太地區成為未來市場發展的關鍵區域。

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  • 企業概況
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  • 區域分類
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    • 根據產品系列、地理覆蓋範圍和策略聯盟對主要企業進行基準分析。

目錄

第1章執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 波特五力分析
    • 供應商的議價能力
    • 買方的議價能力
    • 替代品的威脅
    • 新進入者的威脅
    • 競爭公司之間的競爭
  • 主要企業市佔率分析
  • 產品基準評效和效能比較

第5章：全球情緒辨識市場：按類型分類

  • 臉部表情辨識
  • 語音情緒識別
  • 基於文本的情感識別
  • 透過生理/生物熱訊號進行情緒識別
  • 多模態情緒識別

第6章：全球情緒辨識市場：依組件分類

  • 硬體
  • 軟體
  • 服務

第7章：全球情緒辨識市場：依部署模式分類

  • 現場
  • 雲

第8章：全球情緒辨識市場：依技術分類

  • 機器學習
  • 深度學習
  • 自然語言處理（NLP）
  • 電腦視覺
  • 語音分析

第9章：全球情緒辨識市場：依應用分類

  • 客戶經驗管理
  • 醫療和心理健康監測
  • 汽車和駕駛員監控
  • 零售與電子商務
  • 安全監控
  • 教育和數位學習
  • 媒體與娛樂

第10章：全球情緒辨識市場：依最終用戶分類

  • 公司
  • 政府/國防
  • 醫療服務提供方
  • 其他最終用戶

第11章 全球情緒辨識市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第12章 策略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第13章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第14章：公司簡介

  • Affectiva（Smart Eye）
  • IBM Corporation
  • Microsoft Corporation
  • Google LLC（Alphabet Inc.）
  • Apple Inc.
  • Amazon Web Services Inc.
  • Realeyes OU
  • NVISO SA
  • Eyeris Technologies Inc.
  • Entropik Technologies Pvt. Ltd.
  • Uniphore Technologies Inc.
  • Kairos Inc.
  • Noldus Information Technology BV
  • Beyond Verbal Communication Ltd.
  • Cogito Corporation
Product Code: SMRC34923

According to Stratistics MRC, the Global AI in Emotion Recognition Market is accounted for $2.82 billion in 2026 and is expected to reach $14.771 billion by 2034 growing at a CAGR of 22.9% during the forecast period. Artificial Intelligence in Emotion Recognition refers to the use of advanced machine learning, deep learning, and affective computing techniques to identify, interpret, and respond to human emotions from various data sources such as facial expressions, voice tone, physiological signals, and text. These systems analyze subtle behavioral cues to detect emotional states like happiness, anger, or stress in real time. AI-driven emotion recognition enhances human-computer interaction, enabling more personalized and empathetic responses across applications in healthcare, customer experience, automotive systems, and security, while continuously improving accuracy through data-driven learning models.

Market Dynamics:

Driver:

Rising Demand for Human-Centric AI

The growing emphasis on human-centric artificial intelligence is significantly driving the AI in emotion recognition market. Organizations increasingly seek technologies that enable machines to understand and respond to human emotions, enhancing user experience and engagement. This demand is particularly evident in customer service, healthcare, and automotive applications, where empathetic interactions improve outcomes. Advances in machine learning and affective computing further support this trend, enabling real-time emotional insights and fostering deeper human-machine connections across diverse industries.

Restraint:

Data Privacy and Security Concerns

Data privacy and security concerns remain a major restraint for the AI in emotion recognition market. These systems rely on sensitive personal data, including facial expressions, voice patterns, and biometric signals, raising ethical and regulatory challenges. Stringent data protection laws and increasing public awareness about privacy risks limit widespread adoption. Organizations must invest in secure data handling, anonymization techniques, and compliance frameworks, which can increase operational complexity and costs, thereby slowing the deployment of emotion recognition technologies.

Opportunity:

Expanding Use in Marketing & Customer Analytics

The expanding application of AI in emotion recognition within marketing and customer analytics presents significant growth opportunities. Businesses are leveraging emotion-sensing technologies to gain deeper insights into consumer behavior, preferences, and emotional responses to products or campaigns. This enables highly personalized marketing strategies and improved customer engagement. Real-time emotional feedback helps brands refine advertising effectiveness and enhance user experiences, driving higher conversion rates. As competition intensifies, companies increasingly adopt these tools to gain a strategic advantage.

Threat:

High Implementation and Development Costs

High implementation and development costs pose a considerable threat to the AI in emotion recognition market. Developing accurate and reliable systems requires substantial investment in advanced algorithms, high-quality datasets, and specialized hardware. Integration with existing systems and ongoing maintenance further add to the financial burden. Small and medium-sized enterprises often face challenges in adopting these technologies due to budget constraints, limiting market penetration. Additionally, continuous upgrades are necessary to maintain accuracy and competitiveness, increasing long-term costs.

Covid-19 Impact:

The COVID-19 pandemic had a mixed impact on the AI in emotion recognition market. While disruptions initially slowed investments and deployments, the shift toward digital interactions accelerated demand for emotion-aware technologies. Remote communication, telehealth, and virtual customer engagement increased the need for systems capable of interpreting emotional cues without physical presence. Organizations adopted these solutions to enhance user experience and monitor well-being. Post-pandemic, the market continues to benefit from sustained digital transformation and growing reliance on AI-driven interaction tools.

The facial emotion recognition segment is expected to be the largest during the forecast period

The facial emotion recognition segment is expected to account for the largest market share during the forecast period, due to its widespread adoption and technological maturity. This segment leverages advanced computer vision and deep learning techniques to analyze facial expressions in real time. Its applications span security, retail, healthcare, and automotive industries, where visual emotional cues are critical. The increasing availability of high-resolution cameras and improved algorithm accuracy further support its dominance, making it a preferred solution across various end-user sectors.

The healthcare providers segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the healthcare providers segment is predicted to witness the highest growth rate, due to increasing demand for patient-centric care and mental health monitoring. Emotion recognition technologies assist in identifying psychological conditions, stress levels, and patient responses to treatment. These systems enhance clinical decision-making and improve patient engagement, particularly in telemedicine and remote care settings. Growing investments in digital healthcare infrastructure and AI integration further accelerate adoption, positioning healthcare providers as a key growth segment.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, due to technological infrastructure and early adoption of advanced AI solutions. The presence of leading technology companies and significant investments in research and development contribute to market growth. Additionally, high demand for enhanced customer experience and advanced healthcare solutions supports widespread adoption. Favorable government initiatives and regulatory frameworks further encourage innovation, establishing North America as a dominant region in the AI in emotion recognition market.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, owing to rapid digital transformation and increasing adoption of AI technologies across emerging economies. Growing investments in smart city projects, healthcare innovation, and customer analytics drive market expansion. Countries such as China, Japan, and India are actively integrating emotion recognition systems into various applications. Rising consumer awareness and expanding technological capabilities further accelerate growth, making Asia Pacific a key region for future market development.

Key players in the market

Some of the key players in AI in Emotion Recognition Market include Affectiva, IBM Corporation, Microsoft Corporation, Google LLC (Alphabet Inc.), Apple Inc., Amazon Web Services Inc., Realeyes OU, NVISO SA, Eyeris Technologies Inc., Entropik Technologies Pvt. Ltd., Uniphore Technologies Inc., Kairos Inc., Noldus Information Technology BV, Beyond Verbal Communication Ltd. and Cogito Corporation.

Key Developments:

In February 2026, Wesfarmers and Microsoft announced a multi-year strategic partnership to accelerate AI-powered innovation, focusing on expanding the adoption of Microsoft's AI, cloud, and data technologies across retail and industrial operations, enhancing customer experience, improving supply chain efficiency, and boosting employee productivity through AI-driven tools.

In February 2026, Microsoft and OpenAI reaffirmed their long-standing partnership, emphasizing that it remains strong and unchanged despite new collaborations and investments. Both companies will continue working closely across research, engineering, and product development, with Microsoft retaining access to OpenAI's intellectual property and Azure remaining central to delivering AI solutions, while maintaining flexibility for independent growth.

Types Covered:

  • Facial Emotion Recognition
  • Speech/Voice Emotion Recognition
  • Text-Based Emotion Recognition
  • Physiological/Biosignal Emotion Recognition
  • Multimodal Emotion Recognition

Components Covered:

  • Hardware
  • Software
  • Services

Deployment Modes Covered:

  • On-Premises
  • Cloud

Technologies Covered:

  • Machine Learning
  • Deep Learning
  • Natural Language Processing (NLP)
  • Computer Vision
  • Speech & Voice Analytics

Applications Covered:

  • Customer Experience Management
  • Healthcare & Mental Health Monitoring
  • Automotive & Driver Monitoring
  • Retail & E-commerce
  • Security & Surveillance
  • Education & E-learning
  • Media & Entertainment

End Users Covered:

  • Enterprises
  • Government & Defense
  • Healthcare Providers
  • Other End Users

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global AI in Emotion Recognition Market, By Type

  • 5.1 Facial Emotion Recognition
  • 5.2 Speech/Voice Emotion Recognition
  • 5.3 Text-Based Emotion Recognition
  • 5.4 Physiological/Biosignal Emotion Recognition
  • 5.5 Multimodal Emotion Recognition

6 Global AI in Emotion Recognition Market, By Component

  • 6.1 Hardware
  • 6.2 Software
  • 6.3 Services

7 Global AI in Emotion Recognition Market, By Deployment Mode

  • 7.1 On-Premises
  • 7.2 Cloud

8 Global AI in Emotion Recognition Market, By Technology

  • 8.1 Machine Learning
  • 8.2 Deep Learning
  • 8.3 Natural Language Processing (NLP)
  • 8.4 Computer Vision
  • 8.5 Speech & Voice Analytics

9 Global AI in Emotion Recognition Market, By Application

  • 9.1 Customer Experience Management
  • 9.2 Healthcare & Mental Health Monitoring
  • 9.3 Automotive & Driver Monitoring
  • 9.4 Retail & E-commerce
  • 9.5 Security & Surveillance
  • 9.6 Education & E-learning
  • 9.7 Media & Entertainment

10 Global AI in Emotion Recognition Market, By End User

  • 10.1 Enterprises
  • 10.2 Government & Defense
  • 10.3 Healthcare Providers
  • 10.4 Other End Users

11 Global AI in Emotion Recognition Market, By Geography

  • 11.1 North America
    • 11.1.1 United States
    • 11.1.2 Canada
    • 11.1.3 Mexico
  • 11.2 Europe
    • 11.2.1 United Kingdom
    • 11.2.2 Germany
    • 11.2.3 France
    • 11.2.4 Italy
    • 11.2.5 Spain
    • 11.2.6 Netherlands
    • 11.2.7 Belgium
    • 11.2.8 Sweden
    • 11.2.9 Switzerland
    • 11.2.10 Poland
    • 11.2.11 Rest of Europe
  • 11.3 Asia Pacific
    • 11.3.1 China
    • 11.3.2 Japan
    • 11.3.3 India
    • 11.3.4 South Korea
    • 11.3.5 Australia
    • 11.3.6 Indonesia
    • 11.3.7 Thailand
    • 11.3.8 Malaysia
    • 11.3.9 Singapore
    • 11.3.10 Vietnam
    • 11.3.11 Rest of Asia Pacific
  • 11.4 South America
    • 11.4.1 Brazil
    • 11.4.2 Argentina
    • 11.4.3 Colombia
    • 11.4.4 Chile
    • 11.4.5 Peru
    • 11.4.6 Rest of South America
  • 11.5 Rest of the World (RoW)
    • 11.5.1 Middle East
      • 11.5.1.1 Saudi Arabia
      • 11.5.1.2 United Arab Emirates
      • 11.5.1.3 Qatar
      • 11.5.1.4 Israel
      • 11.5.1.5 Rest of Middle East
    • 11.5.2 Africa
      • 11.5.2.1 South Africa
      • 11.5.2.2 Egypt
      • 11.5.2.3 Morocco
      • 11.5.2.4 Rest of Africa

12 Strategic Market Intelligence

  • 12.1 Industry Value Network and Supply Chain Assessment
  • 12.2 White-Space and Opportunity Mapping
  • 12.3 Product Evolution and Market Life Cycle Analysis
  • 12.4 Channel, Distributor, and Go-to-Market Assessment

13 Industry Developments and Strategic Initiatives

  • 13.1 Mergers and Acquisitions
  • 13.2 Partnerships, Alliances, and Joint Ventures
  • 13.3 New Product Launches and Certifications
  • 13.4 Capacity Expansion and Investments
  • 13.5 Other Strategic Initiatives

14 Company Profiles

  • 14.1 Affectiva (Smart Eye)
  • 14.2 IBM Corporation
  • 14.3 Microsoft Corporation
  • 14.4 Google LLC (Alphabet Inc.)
  • 14.5 Apple Inc.
  • 14.6 Amazon Web Services Inc.
  • 14.7 Realeyes OU
  • 14.8 NVISO SA
  • 14.9 Eyeris Technologies Inc.
  • 14.10 Entropik Technologies Pvt. Ltd.
  • 14.11 Uniphore Technologies Inc.
  • 14.12 Kairos Inc.
  • 14.13 Noldus Information Technology BV
  • 14.14 Beyond Verbal Communication Ltd.
  • 14.15 Cogito Corporation

List of Tables

  • Table 1 Global AI in Emotion Recognition Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI in Emotion Recognition Market Outlook, By Type (2023-2034) ($MN)
  • Table 3 Global AI in Emotion Recognition Market Outlook, By Facial Emotion Recognition (2023-2034) ($MN)
  • Table 4 Global AI in Emotion Recognition Market Outlook, By Speech/Voice Emotion Recognition (2023-2034) ($MN)
  • Table 5 Global AI in Emotion Recognition Market Outlook, By Text-Based Emotion Recognition (2023-2034) ($MN)
  • Table 6 Global AI in Emotion Recognition Market Outlook, By Physiological/Biosignal Emotion Recognition (2023-2034) ($MN)
  • Table 7 Global AI in Emotion Recognition Market Outlook, By Multimodal Emotion Recognition (2023-2034) ($MN)
  • Table 8 Global AI in Emotion Recognition Market Outlook, By Component (2023-2034) ($MN)
  • Table 9 Global AI in Emotion Recognition Market Outlook, By Hardware (2023-2034) ($MN)
  • Table 10 Global AI in Emotion Recognition Market Outlook, By Software (2023-2034) ($MN)
  • Table 11 Global AI in Emotion Recognition Market Outlook, By Services (2023-2034) ($MN)
  • Table 12 Global AI in Emotion Recognition Market Outlook, By Deployment Mode (2023-2034) ($MN)
  • Table 13 Global AI in Emotion Recognition Market Outlook, By On-Premises (2023-2034) ($MN)
  • Table 14 Global AI in Emotion Recognition Market Outlook, By Cloud (2023-2034) ($MN)
  • Table 15 Global AI in Emotion Recognition Market Outlook, By Technology (2023-2034) ($MN)
  • Table 16 Global AI in Emotion Recognition Market Outlook, By Machine Learning (2023-2034) ($MN)
  • Table 17 Global AI in Emotion Recognition Market Outlook, By Deep Learning (2023-2034) ($MN)
  • Table 18 Global AI in Emotion Recognition Market Outlook, By Natural Language Processing (NLP) (2023-2034) ($MN)
  • Table 19 Global AI in Emotion Recognition Market Outlook, By Computer Vision (2023-2034) ($MN)
  • Table 20 Global AI in Emotion Recognition Market Outlook, By Speech & Voice Analytics (2023-2034) ($MN)
  • Table 21 Global AI in Emotion Recognition Market Outlook, By Application (2023-2034) ($MN)
  • Table 22 Global AI in Emotion Recognition Market Outlook, By Customer Experience Management (2023-2034) ($MN)
  • Table 23 Global AI in Emotion Recognition Market Outlook, By Healthcare & Mental Health Monitoring (2023-2034) ($MN)
  • Table 24 Global AI in Emotion Recognition Market Outlook, By Automotive & Driver Monitoring (2023-2034) ($MN)
  • Table 25 Global AI in Emotion Recognition Market Outlook, By Retail & E-commerce (2023-2034) ($MN)
  • Table 26 Global AI in Emotion Recognition Market Outlook, By Security & Surveillance (2023-2034) ($MN)
  • Table 27 Global AI in Emotion Recognition Market Outlook, By Education & E-learning (2023-2034) ($MN)
  • Table 28 Global AI in Emotion Recognition Market Outlook, By Media & Entertainment (2023-2034) ($MN)
  • Table 29 Global AI in Emotion Recognition Market Outlook, By End User (2023-2034) ($MN)
  • Table 30 Global AI in Emotion Recognition Market Outlook, By Enterprises (2023-2034) ($MN)
  • Table 31 Global AI in Emotion Recognition Market Outlook, By Government & Defense (2023-2034) ($MN)
  • Table 32 Global AI in Emotion Recognition Market Outlook, By Healthcare Providers (2023-2034) ($MN)
  • Table 33 Global AI in Emotion Recognition Market Outlook, By Other End Users (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) are also represented in the same manner as above.