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1401312

アフェクティブコンピューティングの世界市場：2023年～2030年

Global Affective Computing Market - 2023-2030
出版日: | 発行: DataM Intelligence | ページ情報: 英文 211 Pages | 納期: 約2営業日

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アフェクティブコンピューティングの世界市場：2023年～2030年
出版日: 2023年12月29日
発行: DataM Intelligence
ページ情報: 英文 211 Pages
納期: 約2営業日
ご注意事項 :
本レポートは最新情報反映のため適宜更新し、内容構成変更を行う場合があります。ご検討の際はお問い合わせください。
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  • 目次
概要

概要

世界のアフェクティブコンピューティング市場は、2022年に509億米ドルに達し、2023-2030年の予測期間中にCAGR 36.2％で成長し、2030年には5,929億米ドルに達すると予測されています。

ディープラーニングにおけるAIとML技術の技術的進歩は、アフェクティブコンピューティングシステムの能力を著しく向上させました。高度なアルゴリズムは現在、複雑な感情的手がかりをより高い精度で分析・解釈します。自然で直感的な人間と機械のインタラクションに対する需要の高まりが、アフェクティブコンピューティングの採用を促進しています。企業や産業界は、機械に感情インテリジェンスを活用することで、ユーザー体験やエンゲージメントを高めています。

ウェアラブルデバイスの普及とモノのインターネットの拡大は、アフェクティブコンピューティングを統合する機会を提供します。感情認識用のセンサーを搭載したウェアラブルデバイスや、感情認識機能を備えたIoTデバイスが市場成長に貢献しています。顧客サービスからバーチャルコンパニオンまで、さまざまな用途でバーチャルアシスタントやチャットボットが広く使用されていることが、効果的なコンピューティングの需要を促進しています。感情を考慮したバーチャルアシスタントは、ユーザーとのインタラクションや満足度を高める。

北米は、パーソナライズされた学習のための教育におけるアフェクティブコンピューティングの使用の増加により、世界のアフェクティブコンピューティング市場で支配的な地域です。この地域はイノベーションと研究開発を重視しており、感情認識、感情分析、アフェクティブコンピューティング・アプリケーションに関連する技術の進歩に貢献しています。北米ではヘルスケア、小売、エンターテイメントなどの産業が早くからアフェクティブコンピューティング・アプリケーションに関心を示し、採用しています。

市場力学

バーチャルアシスタントへの需要の高まり

アフェクティブコンピューティングにより、バーチャルアシスタントはユーザーの感情表現に基づいて応答をパーソナライズすることができます。パーソナライゼーションのレベルは、よりカスタマイズされた魅力的なユーザー体験に貢献します。アフェクティブコンピューティング技術により、バーチャルアシスタントは感情的にインテリジェントな会話エージェントになることができます。ユーザーの感情を認識し反応することで、より自然で共感的なインタラクションを実現します。アフェクティブコンピューティングを搭載したバーチャルアシスタントは、ユーザーの感情状態に基づいてインターフェースや応答を適応させる。この適応性は、ダイナミックでユーザー中心の体験に貢献します。

顧客サービスのアプリケーションでは、アフェクティブコンピューティング機能を備えたバーチャルアシスタントは、顧客の感情や心情をよりよく理解し、対応します。これは特に、問題解決やサポートの提供に役立ちます。アフェクティブコンピューティングは、ユーザーの声から感情を認識することを容易にします。バーチャルアシスタントは、スマートフォン、スマートスピーカー、その他のデバイスのいずれであっても、この機能を使用して、検出された感情のトーンに基づいて応答や対話を調整します。

技術の進歩

機械学習と人工知能の継続的な進歩は、感情認識のより洗練されたアルゴリズムの開発に貢献しています。アルゴリズムの改善により、アフェクティブコンピューティングシステムの精度と効率が向上します。顔認識カメラ、音声認識マイク、生理学的センサーを含むセンサー技術の進歩は、より良いデータの取得と分析に貢献します。センシング技術の向上により、感情的な手がかりのより正確な測定が可能になります。

ディープラーニングとニューラルネットワークの進化は、パターン認識におけるブレークスルーをもたらし、アフェクティブコンピューティングシステムが表情や声のトーン、その他の感情信号の複雑なパターンを識別することを可能にします。技術の進歩により、感情認識のための複数のモダリティの統合が可能になり、例えば、顔の表情と音声分析や生理学的信号を組み合わせることができます。マルチモーダルアプローチは感情分析の包括性を向上させる。

低い精度と信頼性

アフェクティブコンピューティング・システムは、人間の感情を正確に認識・解釈するように設計されたアルゴリズムに大きく依存しています。感情認識の精度が低いと、ユーザーの感情状態を誤って解釈することになり、技術の信頼性に影響します。感情の手がかりの解釈は主観的で文脈に依存します。アフェクティブコンピューティング・アルゴリズムは、個人や状況によって異なる多様な感情表現を一貫して解釈することに苦労しており、結果に一貫性がないです。

人間の感情は複雑で、さまざまな表情で現れるため、感情の全領域を正確にカバーするアルゴリズムを開発するのは困難です。表情の微妙なニュアンスやバリエーションが複雑さに拍車をかけています。感情は文化によって表現が異なり、アフェクティブコンピューティングシステムは必ずしもこのような文化的差異を考慮していません。その結果、特に多様で世界なユーザー集団において、感情的な手がかりを誤って解釈してしまうことになります。

目次

第1章 調査手法と調査範囲

第2章 定義と概要

第3章 エグゼクティブサマリー

第4章 市場力学

  • 影響要因
    • 促進要因
      • バーチャルアシスタント需要の高まり
      • 技術の進歩
    • 抑制要因
      • 精度と信頼性の低さ
    • 機会
    • 影響分析

第5章 産業分析

  • ポーターのファイブフォース分析
  • サプライチェーン分析
  • 価格分析
  • 規制分析
  • ロシア・ウクライナ戦争の影響分析
  • DMIの見解

第6章 COVID-19分析

第7章 技術別

  • タッチベース
  • タッチレス

第8章 コンポーネント別

  • ソフトウェア
    • 音声認識
    • ジェスチャー認識
    • 顔特徴抽出
    • 分析ソフトウェア
    • エンタープライズ・ソフトウェア
  • ハードウェア
    • センサー
    • カメラ
    • ストレージ・デバイスとプロセッサー
    • その他

第9章 企業規模別

  • 中小企業
  • 大企業

第10章 エンドユーザー別

  • 学術・調査
  • メディア・エンターテインメント
  • 政府・防衛
  • ヘルスケア・ライフサイエンス
  • IT・通信
  • 小売・eコマース
  • 自動車
  • BFSI
  • その他

第11章 地域別

  • 北米
    • 米国
    • カナダ
    • メキシコ
  • 欧州
    • ドイツ
    • 英国
    • フランス
    • イタリア
    • スペイン
    • その他欧州
  • 南米
    • ブラジル
    • アルゼンチン
    • その他南米
  • アジア太平洋
    • 中国
    • インド
    • 日本
    • オーストラリア
    • その他アジア太平洋地域
  • 中東・アフリカ

第12章 競合情勢

  • 競合シナリオ
  • 市況/シェア分析
  • M&A分析

第13章 企業プロファイル

  • Amazon Web Services Inc.
    • 会社概要
    • 製品ポートフォリオと説明
    • 財務概要
    • 主な発展
  • Affectiva Inc.
  • Nuance Communications Inc.
  • Nemesysco Ltd.
  • Eyesight Technologies Ltd.
  • Element Human Ltd.
  • Emotibot Technologies Limited
  • Kairos AR, Inc.
  • Realeyes Data Services Ltd.
  • AUDEERING GmbH

第14章 付録

目次
Product Code: ICT7659

Overview

Global Affective Computing Market reached US$ 50.9 Billion in 2022 and is expected to reach US$ 592.9 Billion by 2030, growing with a CAGR of 36.2% during the forecast period 2023-2030.

Technological advancements in AI and ML technologies in deep learning significantly enhanced the capabilities of affective computing systems. Advanced algorithms now analyze and interpret complex emotional cues with greater accuracy. The rising demand for natural and intuitive human-machine interaction is driving the adoption of affective computing. Businesses and industries are leveraging emotional intelligence in machines to enhance user experiences and engagement.

The proliferation of wearable devices and the expansion of the Internet of Things provide opportunities for integrating affective computing. Wearables equipped with sensors for emotion recognition and IoT devices with emotion-aware features contribute to market growth. The widespread use of virtual assistants and chatbots in various applications, from customer service to virtual companions, is fueling the demand for effective computing. Emotionally intelligent virtual assistants enhance user interactions and satisfaction.

North America is a dominating region in the global affective computing market due to the growing use of affective computing in education for personalized learning. The region's emphasis on innovation and research-driven development contributes to the advancement of technologies related to emotion recognition, sentiment analysis and affective computing applications. Industries such as healthcare, retail and entertainment in North America have shown early interest and adoption of affective computing applications.

Dynamics

Growing Demand for Virtual Assistants

Affective computing allows virtual assistants to personalize their responses based on users' emotional expressions. The level of personalization contributes to a more tailored and engaging user experience. Affective computing technologies enable virtual assistants to become emotionally intelligent conversational agents. It recognize and respond to users' emotions, creating a more natural and empathetic interaction. Virtual assistants, powered by affective computing, adapt their interfaces and responses based on users' emotional states. The adaptability contributes to a dynamic and user-centric experience.

In customer service applications, virtual assistants equipped with affective computing capabilities better understand and address customers' emotions and sentiments. The is particularly valuable for resolving issues and providing support. Affective computing facilitates the recognition of emotions in users' voices. Virtual assistants, whether in smartphones, smart speakers or other devices use this capability to tailor responses and interactions based on the detected emotional tone.

Technological Advancement

Ongoing advancements in machine learning and artificial intelligence contribute to the development of more sophisticated algorithms for emotion recognition. Improved algorithms enhance the accuracy and efficiency of affective computing systems. Progress in sensor technologies, including facial recognition cameras, voice recognition microphones and physiological sensors, contributes to better data capture and analysis. Enhanced sensing technologies enable more precise measurement of emotional cues.

The evolution of deep learning and neural networks has led to breakthroughs in pattern recognition, enabling affective computing systems to discern intricate patterns in facial expressions, voice Tons and other emotional signals. Technological advancements enable the integration of multiple modalities for emotion recognition, such as combining facial expressions with voice analysis and physiological signals. The multi-modal approach improves the comprehensiveness of emotional analysis.

Low Accuracy and Reliability

Affective computing systems heavily rely on algorithms designed to recognize and interpret human emotions accurately. Low accuracy in emotion recognition lead to misinterpretation of users' emotional states, affecting the reliability of the technology. The interpretation of emotional cues is subjective and context-dependent. Affective computing algorithms struggle to consistently interpret diverse emotional expressions across different individuals and situations, leading to inconsistencies in results.

Human emotions are complex and manifest in a wide range of expressions, making it challenging to develop algorithms that cover the full spectrum of emotional states accurately. Subtle nuances and variations in expressions add to the complexity. Emotions are expressed differently across cultures and affective computing systems do not always account for these cultural variations. The results in misinterpretations of emotional cues, especially in diverse and global user populations.

Segment Analysis

The global affective computing market is segmented based on technology, component, enterprise size, end-user and region.

Growing Adoption of Touch-based Technology in Affective Computing Market

Based on the technology, the affective computing market is segmented into touch-based and touchless. Touch-based technology is a more natural form of human-computer interaction compared to touchless technology. Touch-based sensors and devices capture subtle nuances in touch interactions, providing a means to recognize and interpret emotional cues. The pressure, duration and patterns of touch convey emotional information, contributing to affective computing applications.

The widespread adoption of smartphones, tablets and wearables has driven the integration of touch-based interfaces. The devices often incorporate touch sensors to facilitate user interactions. The use of affective computing in these devices enhances user experiences, especially in applications related to health and wellness.

Haptic feedback, a component of touch-based technology, allows devices to provide tactile sensations in response to user interactions. The feature enhances emotional engagement by creating a sense of touch, adding an extra dimension to the user experience. Growing product launches in the automotive industry with touch-based affective computing help to boost segment growth over the forecast period.

For instance, on August 15, 2022, Mahindra & Mahindra, India's leading SUV manufacturer launched its new state-of-the-art INGLO EV platform and five e-SUVs under two EV brands showcasing its vision for the future of electric mobility. The brake-by-wire technology is completely decoupled from the hydraulic system; this allows multiple brake modes for pedal feel and recuperation. Its behind the wheel enjoy the Intelligent Drive Modes that govern various aspects including modulation of powertrain response, suspension response, brake feel, electronic stability control intervention and many more features at the touch of a button

Geographical Penetration

North America is a Dominating Affective Computing Market Due To The Rapid Growth In Research

North America accounted for the largest market share in the global affective computing market due to the growing research and innovation in the region. North America is renowned for leading advances in technical innovation. A robust ecosystem of startups, research centers and technology firms exist in the area, all of which actively support the creation and application of efficient computer technologies. Affective computing is an area of study that is heavily researched by renowned research institutions and universities in North America.

Growing technological advancements in the region help to boost the regional market growth. For instance, on August 03, 2022, Gartner identified four emerging technologies expected to have a transformational impact on digital advertising. The four technologies are artificial intelligence (AI) for marketing, emotion AI, influence engineering and generative AI. A technology or application's evolutionary trajectory might be seen through the Gartner Hype Cycle, which offers valuable insights for managing the implementation of a particular business objective.

Competitive Landscape

The major global players in the market include Amazon Web Services Inc., Affectiva Inc., Nuance Communications Inc., Nemesysco Ltd., Eyesight Technologies Ltd., Element Human Ltd., Emotibot Technologies Limited, Kairos AR, Inc., Realeyes Data Services Ltd. and AUDEERING GmbH.

COVID-19 Impact Analysis

The pandemic accelerated the pace of digital transformation across industries as organizations sought to adapt to remote work, virtual communication and changes in consumer behavior. Affective Computing technologies, which focus on understanding and responding to human emotions have found increased relevance in virtual communication tools and customer engagement platforms.

Affective Computing plays a role in healthcare applications, including mental health monitoring and virtual care. With the increased demand for remote healthcare solutions during the pandemic, there could be a growing interest in technologies that facilitate emotional understanding and well-being monitoring.

Remote work and the challenges associated with it, including isolation and stress, prompted organizations to focus on employee well-being. Affective Computing tools that gauge and respond to employee emotions have gained attention in the context of remote workforce management. With changes in consumer behavior and an increased reliance on online services, businesses have looked to affective computing solutions to enhance virtual customer interactions. Understanding customer emotions and preferences becomes crucial in a digital-first environment.

Russia-Ukraine War Impact Analysis

Conflict disrupts supply chains, it impacts the availability of components and materials needed for the production of technology products, including affective computing solutions. Geopolitical tensions contribute to economic uncertainties, affecting business and consumer confidence. The influences investment decisions and purchasing behaviors, potentially impacting the adoption of affective computing technologies.

Governments introduce new regulations or change existing ones in response to geopolitical events. The regulatory changes affect the operations and market conditions for technology companies, including those in the affective computing sector. Geopolitical events influence global market sentiment. Investors respond to uncertainties by adjusting their portfolios, which have broader implications for technology stocks and investments.

The affective computing market, like technology markets, often involves international collaboration and partnerships. Geopolitical tensions affect such collaborations, leading to changes in research and development initiatives. Uncertain geopolitical situations influence consumer behavior. Changes in consumer confidence and spending patterns impact the market demand for affective computing applications, especially in sectors such as retail, entertainment and customer service.

By Technology

  • Touch-based
  • Touchless

By Component

  • Software
    • Speech Recognition
    • Gesture Recognition
    • Facial Feature Extraction
    • Analytics Software
    • Enterprise Software
  • Hardware
    • Sensors
    • Cameras
    • Storage Devices and Processors
    • Others

By Enterprise Size

  • Small and Medium Enterprises
  • Large Enterprises

By End-User

  • Academia and Research
  • Media and Entertainment
  • Government and Defense
  • Healthcare and Life Sciences
  • IT and Telecom
  • Retail and E-Commerce
  • Automotive
  • BFSI
  • Others

By Region

  • North America
    • U.S.
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • France
    • Italy
    • Spain
    • Rest of Europe
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Asia-Pacific
    • China
    • India
    • Japan
    • Australia
    • Rest of Asia-Pacific
  • Middle East and Africa

Key Developments

  • On May 05, 2021, Affectiva acquired Smart Eye, the global leader in eye tracking and driver monitoring systems. By merging their highly skilled teams and industry-leading technologies they bring to market unmatched AI solutions for the automotive industry and media analytics.
  • On February 23, 2021, IBM announced the deployment of "PROPEL-i," a customized end-to-end cloud-native logistics platform created in partnership with IBM Global Business Services, by Safe Xpress, the top supply chain and logistics firm in India.
  • On May 25, 2023, to help clients select investments, JPMorgan created a ChatGPT-like software program that uses a cutting-edge kind of artificial intelligence. The corporation applied to trademark a product named IndexGPT, as per a document from the bank located in New York.

Why Purchase the Report?

  • To visualize the global affective computing market segmentation based on technology, component, enterprise size, end-user and region, as well as understand key commercial assets and players.
  • Identify commercial opportunities by analyzing trends and co-development.
  • Excel data sheet with numerous data points of affective computing market-level with all segments.
  • PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
  • Product mapping available as excel consisting of key products of all the major players.

The global affective computing market report would provide approximately 69 tables, 70 figures and 211 Pages.

Target Audience 2023

  • Manufacturers/ Buyers
  • Industry Investors/Investment Bankers
  • Research Professionals
  • Emerging Companies

Table of Contents

1. Methodology and Scope

  • 1.1. Research Methodology
  • 1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

  • 3.1. Snippet by Technology
  • 3.2. Snippet by Component
  • 3.3. Snippet by Enterprise Size
  • 3.4. Snippet by End-User
  • 3.5. Snippet by Region

4. Dynamics

  • 4.1. Impacting Factors
    • 4.1.1. Drivers
      • 4.1.1.1. Growing Demand for Virtual Assistants
      • 4.1.1.2. Technological Advancement
    • 4.1.2. Restraints
      • 4.1.2.1. Low Accuracy and Reliability
    • 4.1.3. Opportunity
    • 4.1.4. Impact Analysis

5. Industry Analysis

  • 5.1. Porter's Five Force Analysis
  • 5.2. Supply Chain Analysis
  • 5.3. Pricing Analysis
  • 5.4. Regulatory Analysis
  • 5.5. Russia-Ukraine War Impact Analysis
  • 5.6. DMI Opinion

6. COVID-19 Analysis

  • 6.1. Analysis of COVID-19
    • 6.1.1. Scenario Before COVID
    • 6.1.2. Scenario During COVID
    • 6.1.3. Scenario Post COVID
  • 6.2. Pricing Dynamics Amid COVID-19
  • 6.3. Demand-Supply Spectrum
  • 6.4. Government Initiatives Related to the Market During Pandemic
  • 6.5. Manufacturers Strategic Initiatives
  • 6.6. Conclusion

7. By Technology

  • 7.1. Introduction
    • 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
    • 7.1.2. Market Attractiveness Index, By Technology
  • 7.2. Touch-based*
    • 7.2.1. Introduction
    • 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 7.3. Touchless

8. By Component

  • 8.1. Introduction
    • 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 8.1.2. Market Attractiveness Index, By Component
  • 8.2. Software*
    • 8.2.1. Introduction
    • 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
      • 8.2.2.1. Speech Recognition
      • 8.2.2.2. Gesture Recognition
      • 8.2.2.3. Facial Feature Extraction
      • 8.2.2.4. Analytics Software
      • 8.2.2.5. Enterprise Software
  • 8.3. Hardware
    • 8.3.1. Sensors
    • 8.3.2. Cameras
    • 8.3.3. Storage Devices and Processors
    • 8.3.4. Others

9. By Enterprise Size

  • 9.1. Introduction
    • 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Enterprise Size
    • 9.1.2. Market Attractiveness Index, By Enterprise Size
  • 9.2. Small and Medium Enterprises*
    • 9.2.1. Introduction
    • 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 9.3. Large Enterprises

10. By End-User

  • 10.1. Introduction
    • 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 10.1.2. Market Attractiveness Index, By End-User
  • 10.2. Academia and Research*
    • 10.2.1. Introduction
    • 10.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 10.3. Media and Entertainment
  • 10.4. Government and Defense
  • 10.5. Healthcare and Life Sciences
  • 10.6. IT and Telecom
  • 10.7. Retail and E-Commerce
  • 10.8. Automotive
  • 10.9. BFSI
  • 10.10. Others

11. By Region

  • 11.1. Introduction
    • 11.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
    • 11.1.2. Market Attractiveness Index, By Region
  • 11.2. North America
    • 11.2.1. Introduction
    • 11.2.2. Key Region-Specific Dynamics
    • 11.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
    • 11.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Enterprise Size
    • 11.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 11.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.2.7.1. U.S.
      • 11.2.7.2. Canada
      • 11.2.7.3. Mexico
  • 11.3. Europe
    • 11.3.1. Introduction
    • 11.3.2. Key Region-Specific Dynamics
    • 11.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
    • 11.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Enterprise Size
    • 11.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 11.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.3.7.1. Germany
      • 11.3.7.2. UK
      • 11.3.7.3. France
      • 11.3.7.4. Italy
      • 11.3.7.5. Spain
      • 11.3.7.6. Rest of Europe
  • 11.4. South America
    • 11.4.1. Introduction
    • 11.4.2. Key Region-Specific Dynamics
    • 11.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
    • 11.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Enterprise Size
    • 11.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 11.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.4.7.1. Brazil
      • 11.4.7.2. Argentina
      • 11.4.7.3. Rest of South America
  • 11.5. Asia-Pacific
    • 11.5.1. Introduction
    • 11.5.2. Key Region-Specific Dynamics
    • 11.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
    • 11.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Enterprise Size
    • 11.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 11.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.5.7.1. China
      • 11.5.7.2. India
      • 11.5.7.3. Japan
      • 11.5.7.4. Australia
      • 11.5.7.5. Rest of Asia-Pacific
  • 11.6. Middle East and Africa
    • 11.6.1. Introduction
    • 11.6.2. Key Region-Specific Dynamics
    • 11.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
    • 11.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Enterprise Size
    • 11.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User

12. Competitive Landscape

  • 12.1. Competitive Scenario
  • 12.2. Market Positioning/Share Analysis
  • 12.3. Mergers and Acquisitions Analysis

13. Company Profiles

  • 13.1. Amazon Web Services Inc.*
    • 13.1.1. Company Overview
    • 13.1.2. Product Portfolio and Description
    • 13.1.3. Financial Overview
    • 13.1.4. Key Developments
  • 13.2. Affectiva Inc.
  • 13.3. Nuance Communications Inc.
  • 13.4. Nemesysco Ltd.
  • 13.5. Eyesight Technologies Ltd.
  • 13.6. Element Human Ltd.
  • 13.7. Emotibot Technologies Limited
  • 13.8. Kairos AR, Inc.
  • 13.9. Realeyes Data Services Ltd.
  • 13.10. AUDEERING GmbH

LIST NOT EXHAUSTIVE

14. Appendix

  • 14.1. About Us and Services
  • 14.2. Contact Us