感情検出・認識市場：コンポーネント、ツール、技術、用途、エンドユーザー産業、地域別、2026～2032年

感情検出・認識市場の評価-2026～2032年

人工知能と機械学習技術の進歩が感情検出・認識（EDR）市場を牽引しており、ヘルスケア、小売、自動車など様々な産業における感情識別システムの精度と応用を向上させています。Verified Market Researchのアナリストによると、感情検出・認識市場は、2024年には954億1,000万米ドルの評価を下回り、予測期間中に382億6,000万米ドルの評価に達すると推定されています。

カスタマイズ型ユーザーエクスペリエンスへのニーズの高まりと、インタラクティブエンターテイメント、カスタマーサポート、メンタルヘルスモニタリングにおける感情分析の応用が、感情検出・認識市場を牽引しています。これにより、市場は2026～2032年にかけてCAGR 12.1％で成長します。

感情検出・認識市場定義/概要

感情検出・認識とは、表情、声のトーン、テキスト分析など複数のモダリティを使用して人間の感情を識別・理解する技術技術です。このセグメントでは、強力なアルゴリズムと機械学習アプローチを使用して、写真、音声、テキストからのデータを分析し、システムが喜び、悲しみ、怒り、驚きなどの感情を認識できるようにします。

さらに、ヘルスケアにおけるメンタルヘルスのモニタリング、カスタマーサービスにおけるユーザー体験の向上、教育におけるパーソナライズされた学習、ゲームや仮想現実におけるより魅力的なインタラクティブ体験の創造など、感情検出と認識には幅広い用途があります。

市場の成長を促す主要因とは？

顧客体験の向上が重視されるようになり、感情検出・認識技術の導入が加速しています。Gartner社の調査によると、2020年には10％以下だった顧客サービスに、2025年までに50％の組織がAIを活用したチャットボットを利用するようになるといいます。こうしたAIシステムの多くは、感情検出を利用してより共感的で個別化された回答を行い、感情検出・認識市場を押し上げます。

自動車セグメントでは、ドライバーの安全性と体験を向上させるため、感情検出技術の採用が進んでいます。欧州交通安全評議会の調査によると、欧州の交通事故の約30％はドライバーの注意力と疲労によるものです。このため、感情や注意レベルを検出できる先進的ドライバー・モニタリングデバイスに対する需要が増加しており、感情検出・認識市場の成長を牽引しています。

さらに、メンタルヘルスに対する世界の注目は、ヘルスケア用途における感情検出技術の使用を増加させています。世界保健機関（WHO）によると、うつ病は2021年までに世界で約2億8,000万人に影響を及ぼすとされています。メンタルヘルスに関する懸念の蔓延は、早期診断とモニタリングのための感情検出ツールの開発を促進し、市場成長に大きく寄与しています。

データセキュリティとプライバシーの懸念は市場の成長をどのように制限するか？

感情データの収集と分析は、プライバシーに関する深刻な懸念を引き起こします。多くの人々は、自分の感情が追跡され記録されることを懸念しています。欧州のGDPRやカリフォルニア州のCCPAといった厳しいデータ保護規制は、企業が感情データを収集、保管、利用する方法を制限しており、市場の成長と受容を妨げています。

感情検出技術は、さまざまな集団の複雑な人間の感情を効果的に識別する上で、継続的なハードルに直面しています。文化的差異、感情の表れ方の個人差、人間の感情の複雑な性質のために、誤解が生じます。このような精度の限界は、技術に対する信頼を損ない、本質的な用途への普及を妨げます。

さらに、感情検出技術の使用は、操作や乱用に関する倫理的問題を引き起こします。この技術がモニタリングや対象広告に使われたり、本人の認識や同意なしに人々の行動に影響を与えたりすることが懸念されます。こうした倫理的な問題は、モニタリングや規制の強化につながり、特定の産業における市場拡大を阻害する可能性があります。

目次

第1章 イントロダクション

• 市場の定義
• 市場セグメンテーション
• 調査手法

第2章 エグゼクティブサマリー

• 主要調査結果
• 市場概要
• 市場ハイライト

第3章 市場概要

• 市場規模と成長の可能性
• 市場動向
• 市場促進要因
• 市場抑制要因
• 市場機会
• ポーターのファイブフォース分析

第4章 感情検出・認識市場：技術別

• バイオセンサ技術
• 機械学習
• パターン認識
• 特徴抽出
• 自然言語処理

第5章 感情検出・認識市場：用途別

• モニタリング・モニタリング
• マーケティングと広告
• ロボット工学とeラーニング
• 緊急医療
• その他

第6章 感情検出・認識市場：エンドユーザー別

• 銀行、金融サービス、保険（BFSI）
• ヘルスケアとライフサイエンス
• ITとテレコム
• 小売・eコマース
• 教育
• メディアとエンターテインメント
• 自動車
• その他

第7章 感情検出・認識市場：コンポーネント別

• ソフトウェア
• サービス

第8章 地域別分析

• 北米
• 米国
• カナダ
• メキシコ
• 欧州
• 英国
• ドイツ
• フランス
• イタリア
• アジア太平洋
• 中国
• 日本
• インド
• オーストラリア
• ラテンアメリカ
• ブラジル
• アルゼンチン
• チリ
• 中東・アフリカ
• 南アフリカ
• サウジアラビア
• アラブ首長国連邦

第9章 市場力学

• 市場促進要因
• 市場抑制要因
• 市場機会
• COVID-19の市場への影響

第10章 競合情勢

• 主要企業
• 市場シェア分析

第11章 企業プロファイル

• Affectiva
• Amazon.com, Inc.
• Apple Inc.
• Cognitec
• Eyeris
• Google
• IBM Corporation
• iMotions
• Kairos AR, Inc.
• NEC Corporation
• Noldus Information Technology BV
• NVISO
• Realeyes
• Sentiance
• Sightcorp
• SkyBiometry
• Tobii
• Q3 Technologies Inc.
• Paravision Inc.

第12章 市場展望市場展望と機会

• 新興技術
• 今後の市場動向
• 投資機会

第13章 付録

• 略語リスト
• 供給源と参考文献

Emotion Detection and Recognition Market Valuation - 2026-2032

The advancements in artificial intelligence and machine learning technologies are driving the emotion detection and recognition (EDR) market, which improves the accuracy and application of emotion identification systems in a variety of industries such as healthcare, retail, and automotive. According to the analyst from Verified Market Research, the emotion detection and recognition market is estimated to reach a valuation of USD 38.26 Billion over the forecast subjugating around USD 95.41 Billion valued in 2024.

The growing need for customized user experiences and the application of emotion analytics in interactive entertainment, customer support, and mental health monitoring are driving the emotion detection and recognition market. It enables the market to grow at a CAGR of 12.1% from 2026 to 2032.

Emotion Detection and Recognition Market: Definition/ Overview

Emotion detection and recognition is the technological technique of identifying and understanding human emotions using multiple modalities such as facial expressions, vocal tones, and textual analysis. This field uses powerful algorithms and machine learning approaches to analyze data from photos, audio, and text, allowing systems to recognize emotions like happiness, sadness, rage, and surprise.

Furthermore, emotion detection and recognition have a wide range of applications, including monitoring mental health in healthcare, improving user experience in customer service, personalized learning in education, and creating more engaging interactive experiences in gaming and virtual reality.

What are the Major Factors Driving the Growth of the Market?

The rising emphasis on improving the customer experience is accelerating the deployment of emotion detection and recognition technologies. According to Gartner research, by 2025, 50% of organizations will utilize AI-powered chatbots for customer service, up from less than 10% in 2020. Many of these AI systems use emotion detection to give more empathic and individualized answers, boosting the emotion detection and recognition market.

The automotive sector is progressively adopting emotion-detecting technology to improve driver safety and experience. According to research conducted by the European Transport Safety Council, driver attention and fatigue account for almost 30% of all traffic accidents in Europe. This has led to an increase in demand for advanced driver monitoring devices that can detect emotions and alertness levels, driving growth in the emotion detection and recognition market.

Furthermore, the global focus on mental health is increasing the use of emotion detection technologies in healthcare applications. According to the World Health Organization, depression will affect around 280 million people globally by 2021. The prevalence of mental health concerns is driving the development of emotion detection tools for early diagnosis and monitoring, which is considerably contributing to market growth.

How Does Data Security and Privacy Concerns Restrict the Growth of the Market?

The collection and analysis of emotional data raise serious privacy concerns. Many people are concerned with the thought of having their emotions tracked and recorded. Strict data protection regulations, such as GDPR in Europe and the CCPA in California, restrict how corporations can gather, keep, and use emotional data, thus impeding market growth and acceptance.

Emotion detection technology faces ongoing hurdles in effectively identifying complex human emotions across varied populations. Misinterpretations occur due to cultural variances, individual variability in emotional presentation, and the complicated nature of human emotions. These accuracy limitations undermine trust in the technology and prevent widespread adoption in essential applications.

Furthermore, the use of emotion-detecting technologies raises ethical problems around manipulation and abuse. There are concerns that the technology may be used for surveillance, targeted advertising, or to influence people's behavior without their knowledge or agreement. These ethical quandaries lead to increasing scrutiny and regulation, potentially impeding market expansion in particular industries.

Category-Wise Acumens

What Factors Contribute to the Dominance of the Emotion Detection & Recognition Software?

According to VMR analysis, the software segment is estimated to hold the largest market share during the forecast period. Emotion detection software is highly scalable, allowing organizations to quickly incorporate it into their existing systems and increase usage across numerous platforms. Its adaptability allows for customization in a wide range of applications, including customer service and healthcare. This versatility makes software solutions more appealing to a diverse range of businesses, resulting in widespread adoption and commercial supremacy.

Emotion detection software uses AI and machine learning algorithms to continuously enhance accuracy and performance through data analysis. This self-improvement nature ensures that software solutions keep up with the most recent breakthroughs in emotion identification technologies, ensuring their relevance and efficacy over time. This element makes a substantial contribution to the software segment's market dominance.

Furthermore, software for emotion detection and recognition is frequently less expensive to implement and maintain than hardware-based solutions. Cloud-based software solutions, in particular, eliminate the requirement for a large on-premises infrastructure. This cost-effectiveness makes software solutions more accessible to organizations of all sizes, resulting in increased adoption and market share.

What are the Key Drivers that Propel the Demand for Such Data for Marketing and Advertising?

The marketing and advertising segment is estimated to dominate the emotion detection and recognition market during the forecast period. Emotion detection technology enables marketers to measure real-time emotional reactions to commercials, allowing them to build more engaging and effective campaigns. This feature enables organizations to adapt their messaging to trigger specific emotions, resulting in increased brand memory and client loyalty. The possibility for greater ROI encourages widespread adoption in this area.

Marketers can tailor information and recommendations to specific consumers by evaluating their emotional responses. This level of customization boosts user experience, engagement, and conversion rates. The ability to produce emotionally engaging material at scale drives adoption in marketing and advertising applications.

Furthermore, emotion detection gives marketers vital information about consumer behavior and preferences. This data enables more educated decisions about campaign strategy, product development, and customer service enhancements. The ability to optimize marketing efforts across many channels using data promotes this segment's market domination.

Country/Region-wise Acumens

Will North America Maintain its Dominance in the Market?

According to VMR analyst, North America is estimated to dominate the emotion detection and recognition market during the forecast period. North America is the leader in AI and machine learning adoption, which is critical for emotion detection and identification systems. According to a National Science Foundation estimate, US federal funding for AI research and development surged by more than 40% between 2015 and 2020, reaching almost $1.9 billion in 2020. This investment is fueling innovation in emotion recognition technology.

The North American healthcare industry is increasingly using emotion detection for mental health assessments and patient care. According to the National Institute of Mental Health, an estimated 52.9 million adults in the United States suffered from a mental illness in 2020, accounting for 21% of all adults. This large population necessitates better emotion detection systems in healthcare settings.

Furthermore, the automotive sector in North America is using emotion detection technologies to improve driver safety. According to the National Highway Traffic Safety Administration (NHTSA), motor vehicle traffic crashes killed an estimated 38,824 people in the United States in 2020. This frightening trend is prompting automakers to develop advanced driver monitoring systems that include emotion detection to improve road safety.

What Influences the Steady Expansion of the Emotion Detection and Recognition Market in Asia Pacific?

The Asia Pacific region is estimated to exhibit the highest growth during the forecast period. The Asia Pacific region is experiencing an increase in the usage of AI and machine learning technologies, which are critical for emotion detection and identification systems. According to an IDC estimate, AI spending in the Asia-Pacific region (excluding Japan) is predicted to reach USD 32 Billion by 2025, with a compound annual growth rate (CAGR) of 30.8% between 2020 and 2025. Increased investment in AI technology is expected to fuel growth in the emotion detection and recognition market.

Furthermore, the extensive use of smartphones in the Asia-Pacific region creates an important platform for emotion detection and recognition technology. According to GSMA's Mobile Economy Asia Pacific 2022 report, the area is predicted to have 3.1 billion smartphone connections by 2025, accounting for 83% of the total connections. This large user base creates ample opportunities for emotion detection applications in mobile devices.

Competitive Landscape

The competitive landscape of the emotion detection and recognition market is distinguished by rapid technology breakthroughs and a wide range of applications across various sectors. Companies are boosting their investments in artificial intelligence and machine learning to improve the accuracy and efficiency of emotion recognition systems.

Some of the prominent players operating in the emotion detection and recognition market include:

Affectiva

com, Inc.

Apple, Inc.

Cognitec

Eyeris

Google

IBM Corporation

iMotions

Kairos AR, Inc.

NEC Corporation

Noldus Information Technology BV

NVISO

Realeyes

Sentiance

Sightcorp

SkyBiometry

Tobii

Q3 Technologies, Inc.

Paravision, Inc.

Emotion Detection And Recognition Market Latest Developments

In February 2022, NEC strengthened its strategic relationship with SAP to accelerate NEC's corporate transformation (CX) and co-create business opportunities. It will use the latest SAP technologies to accelerate CX, based on the results of the SAP reforms it has implemented solutions.

In February 2022, IBM purchased Neudesic, a renowned US cloud services firm focused mostly on the Microsoft Azure platform and offering expertise in multi-cloud. This acquisition expands IBM's offering of hybrid multi-cloud services and advances the company's hybrid cloud and AI strategy.

Emotion Detection and Recognition Market, By Category

• Component:
• Software
• Services
• Tools:
• Facial Recognition
• Speech and Voice Recognition
• Gesture and Posture Recognition
• Technology:
• Bio-sensors Technology
• Machine Learning
• Pattern Recognition
• Feature Extraction
• Natural Language Processing
• Application:
• Surveillance and Monitoring
• Marketing and Advertising
• Robotics and eLearning
• Medical Emergency
• Others
• End-User Industry:
• Banking, Financial Services and Insurance (BFSI)
• Healthcare and Life Sciences
• IT and Telecom
• Retail and E-commerce
• Education
• Media and Entertainment
• Automotive
• Others
• Region:
• North America
• Europe
• Asia-Pacific
• South America
• Middle East & Africa

TABLE OF CONTENTS

1.Introduction

• Market Definition
• Market Segmentation
• Research Methodology

2.Executive Summary

• Key Findings
• Market Overview
• Market Highlights

3. Market Overview

• Market Size and Growth Potential
• Market Trends
• Market Drivers
• Market Restraints
• Market Opportunities
• Porter's Five Forces Analysis

4. Emotion Detection And Recognition Market, By Technology

• Bio-sensors Technology
• Machine Learning
• Pattern Recognition
• Feature Extraction
• Natural Language Processing

5. Emotion Detection And Recognition Market, By Application

• Surveillance and Monitoring
• Marketing and Advertising
• Robotics and eLearning
• Medical Emergency
• Others

6.Emotion Detection And Recognition Market, By End-User

• Banking, Financial Services and Insurance (BFSI)
• Healthcare and Life Sciences
• IT and Telecom
• Retail and E-commerce
• Education
• Media and Entertainment
• Automotive
• Others

7. Emotion Detection And Recognition Market, By Component

• Software
• Services

8. Regional Analysis

• North America
• United States
• Canada
• Mexico
• Europe
• United Kingdom
• Germany
• France
• Italy
• Asia-Pacific
• China
• Japan
• India
• Australia
• Latin America
• Brazil
• Argentina
• Chile
• Middle East and Africa
• South Africa
• Saudi Arabia
• UAE

9. Market Dynamics

• Market Drivers
• Market Restraints
• Market Opportunities
• Impact of COVID-19 on the Market

10. Competitive Landscape

• Key Players
• Market Share Analysis

11. Company Profiles

• Affectiva
• Amazon.com, Inc.
• Apple Inc.
• Cognitec
• Eyeris
• Google
• IBM Corporation
• iMotions
• Kairos AR, Inc.
• NEC Corporation
• Noldus Information Technology BV
• NVISO
• Realeyes
• Sentiance
• Sightcorp
• SkyBiometry
• Tobii
• Q3 Technologies Inc.
• Paravision Inc.

12. Market Outlook and Opportunities

• Emerging Technologies
• Future Market Trends
• Investment Opportunities

13. Appendix

• List of Abbreviations
• Sources and References