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市場調查報告書

商品編碼

1733681

2026 年至 2032 年情緒偵測與識別市場（按組件、工具、技術、應用、最終用戶產業和地區分類）

Emotion Detection and Recognition Market By Component, Tools, Technology, Application, End-User Industry, & Region for 2026-2032

出版日期: 2025年04月29日 | 出版商:

Verified Market Research | 英文 205 Pages | 商品交期: 2-3個工作天內

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簡介目錄

情緒偵測與辨識市場評估（2026-2032）

人工智慧和機器學習技術的進步正在推動情緒檢測和識別 (EDR) 市場的發展，提高情緒識別系統在醫療保健、零售和汽車等各個行業的準確性和應用。據 Verified Market Research 分析師稱，情緒檢測和識別市場規模預計將在 2024 年下降至 954.1 億美元，預測期內達到 382.6 億美元的估值。

對客製化使用者體驗的需求不斷成長以及情緒分析在互動娛樂、客戶支援和心理健康監測中的應用正在推動情緒檢測和識別市場的發展。這將有助於市場在 2026 年至 2032 年期間以 12.1% 的複合年成長率成長。

情緒檢測與識別市場定義/概述

情緒檢測和識別是一種使用多種模式（包括面部表情、語調和文字分析）來識別和理解人類情緒的技術。這部分使用強大的演算法和機器學習方法來分析來自照片、語音和文字的數據，使系統能夠識別喜悅、悲傷、憤怒和驚訝等情緒。

此外，情緒檢測和識別具有廣泛的應用，包括醫療保健中的心理健康監測、客戶服務中的用戶體驗改善、教育中的個人化學習以及在遊戲和虛擬實境中創造更具吸引力的互動體驗。

推動市場成長的關鍵因素有哪些？

對改善客戶體驗的日益關注正在加速情緒檢測和識別技術的採用。根據 Gartner 的一項調查，到 2025 年，50% 的組織將使用人工智慧聊天機器人進行客戶服務，而 2020 年這一比例還不到 10%。許多此類人工智慧系統將使用情緒檢測來提供更具同理心和個人化的回應，從而推動情緒檢測和識別市場的發展。

汽車領域擴大採用情緒檢測技術來提高駕駛員的安全性和體驗。根據歐洲道路安全委員會的研究，歐洲約30%的道路交通事故是由於駕駛注意力不集中和疲勞所造成的。這增加了對能夠檢測情緒和注意力水平的先進駕駛員監控設備的需求，從而推動了情緒檢測和識別市場的成長。

此外，全球對心理健康的關注導致情緒檢測技術在醫療保健應用中的使用增加。根據世界衛生組織 (WHO) 的數據，到 2021 年，憂鬱症將影響全球約 2.8 億人。精神健康問題的普遍性促使人們開發情緒檢測工具以進行早期診斷和監測，這對市場成長做出了重大貢獻。

資料安全和隱私問題將如何限制市場成長？

收集和分析情緒資料引發了嚴重的隱私問題。許多人擔心自己的情緒被追蹤和記錄。歐洲的 GDPR 和加州的 CCPA 等嚴格的資料保護條例限制了公司收集、儲存和使用情緒資料的方式，阻礙了市場成長和接受度。

情緒檢測技術在有效識別不同人群的複雜人類情緒方面面臨持續的障礙。誤解的產生是由於文化差異、個人情感表達方式的差異以及人類情感的複雜性。這些準確性限制削弱了人們對該技術的信心，並阻礙了其在重要應用中的廣泛使用。

此外，情緒檢測技術的使用引發了有關操縱和濫用的道德問題。人們擔心這項技術可能被用來監控和定位廣告，或在人們不知情或未經同意的情況下影響人們的行為。這些道德問題可能會導致監控和監管的加強，從而阻礙某些行業的市場擴張。

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.