Global Automatic Content Recognition research

Automatic Content Recognition Comprehensive Study by Type (Acoustic & digital video fingerprinting, Digital audio, video & image watermarking, Optical character recognition, Speech recognition), Application (Consumer Electronics, E-commerce, Education, Automotive, IT & telecommunication, Healthcare, Defense & public safety, Avionics, Others) Players and Region - Global Market Outlook to 2028

Automatic Content Recognition Market by XX Submarkets | Forecast Years 2023-2028  

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  • Summary
  • Market Segments
  • Table of Content
  • List of Table & Figures
  • Players Profiled
Global Automatic Content Recognition Market Overview:
From the earliest days of the internet to the latest era of digitalization. The Automatic Content Recognition is emerging and upending the way television has always been measured as an advertising medium. ACR is an identification technology to recognize content played on media, it reads pixels on smart, internet-connected devices screen as it delivers content to a TV consumer.

AttributesDetails
Study Period2018-2028
Base Year2022
Forecast Period2023-2028
Historical Period2018-2022
UnitValue (USD Million)
Customization ScopeAvail customization with purchase of this report. Add or modify country, region & or narrow down segments in the final scope subject to feasibility


Influencing Trend:
Rise of Consumer Preferences

Market Growth Drivers:
Increasing Integration of ACR in Smart TVs and Second Screen Devices Such as Smartphones and Wearables, Increasing Deployment of ACR Technologies By Media Companies for Applications Such as Broadcast Monitoring and Audience Measurement and Revenue Generated Benefits of Interactivity, Personalization, and Socialization Imparted By the ACR Technology to the Television Environment

Challenges:
Overcoming the Loopholes in ACR Technologies and Technological Challenges and Complexity of Devising Content Recognition Algorithms

Restraints:
Privacy and Security Concerns

Opportunities:
The Evolving Concept of Contextual Advertising, Contextual Commerce, Enhanced Contextual Experiences, and Spoiler-Proof Social Feeds

Competitive Landscape:

Some of the key players profiled in the report are Arcsoft, Inc. (United States), Google, Inc. (United States), Microsoft Corporation (United States), iPharro Media GmbH (Germany), Digimarc Corporation (United States), Nuance communications (United States), Audible Magic Corporation (United States), Civolution (United States), Enswers, Inc. (South Korea), Gracenote, Inc. (United States), Mufin GmBH (Germany), Shazam Entertainment Ltd. (United Kingdom), Vobile, Inc. (United States), Beatgrid Media BV (The Netherlands), Clarifai, Inc. (United States) and VoiceBase, Inc. (United States). Additionally, following companies can also be profiled that are part of our coverage like ACRCloud (China), DataScouting (Greece), Viscovery Pte Ltd (Taiwan) and Voiceinteraction SA (Portugal). Analyst at AMA Research see United States Players to retain maximum share of Global Automatic Content Recognition market by 2028.

Latest Market Insights:
In April 2019, otBC, a company innovating the music industry's rights approval and tracking process, partnered with Digimarc Corporation to offer Digimarc Barcode for Audio, an advanced digital audio watermarking technology within dotBC products. The solution links metadata and copyright ownership information provided by artists, composers, and copyright holders to the audio file itself. This collaboration allowed the industry to easily and accurately identify blockchain addresses and up-to-date ownership data via audio files delivered to digital service providers such as Spotify, Apple, Amazon, Pandora, and more.

In September 2020, Nuance Communications Inc., an Ambient Clinical Intelligence (ACI) solution, and Microsoft Corp. The Nuance Dragon Ambient eXperience is now integrated into Microsoft Teams to broadly expand virtual consulting aimed at improving physician health and delivering better patient health outcomes.

What Can be Explored with the Automatic Content Recognition Market Study
 Gain Market Understanding
 Identify Growth Opportunities
 Analyze and Measure the Global Automatic Content Recognition Market by Identifying Investment across various Industry Verticals
 Understand the Trends that will drive Future Changes in Automatic Content Recognition
 Understand the Competitive Scenario
- Track Right Markets
- Identify the Right Verticals

Research Methodology:
The top-down and bottom-up approaches are used to estimate and validate the size of the Global Automatic Content Recognition market.
In order to reach an exhaustive list of functional and relevant players various industry classification standards are closely followed such as NAICS, ICB, SIC to penetrate deep in important geographies by players and a thorough validation test is conducted to reach most relevant players for survey in Automatic Content Recognition market.
In order to make priority list sorting is done based on revenue generated based on latest reporting with the help of paid databases such as Factiva, Bloomberg etc.
Finally the questionnaire is set and specifically designed to address all the necessities for primary data collection after getting prior appointment by targeting key target audience that includes Automatic content recognition solution providers, Media & entertainment companies, Technology (Fingerprinting, watermarking, OCR, and speech recognition) providers, Consumer electronics companies, Cloud solution providers, Second screen device manufacturers, Professional & managed service providers, System integrators, Technology consultants, E-commerce companies, Automobile manufacturers, Defense & public safety organizations and Others.
This helps us to gather the data related to players revenue, operating cycle and expense, profit along with product or service growth etc.
Almost 70-80% of data is collected through primary medium and further validation is done through various secondary sources that includes Regulators, World Bank, Association, Company Website, SEC filings, OTC BB, USPTO, EPO, Annual reports, press releases etc.

Report Objectives / Segmentation Covered

By Type
  • Acoustic & digital video fingerprinting
  • Digital audio, video & image watermarking
  • Optical character recognition
  • Speech recognition
By Application
  • Consumer Electronics
  • E-commerce
  • Education
  • Automotive
  • IT & telecommunication
  • Healthcare
  • Defense & public safety
  • Avionics
  • Others
By Regions
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Taiwan
    • Australia
    • Rest of Asia-Pacific
  • Europe
    • Germany
    • France
    • Italy
    • United Kingdom
    • Netherlands
    • Rest of Europe
  • MEA
    • Middle East
    • Africa
  • North America
    • United States
    • Canada
    • Mexico
  • 1. Market Overview
    • 1.1. Introduction
    • 1.2. Scope/Objective of the Study
      • 1.2.1. Research Objective
  • 2. Executive Summary
    • 2.1. Introduction
  • 3. Market Dynamics
    • 3.1. Introduction
    • 3.2. Market Drivers
      • 3.2.1. Increasing Integration of ACR in Smart TVs and Second Screen Devices Such as Smartphones and Wearables
      • 3.2.2. Increasing Deployment of ACR Technologies By Media Companies for Applications Such as Broadcast Monitoring and Audience Measurement
      • 3.2.3. Revenue Generated Benefits of Interactivity, Personalization, and Socialization Imparted By the ACR Technology to the Television Environment
    • 3.3. Market Challenges
      • 3.3.1. Overcoming the Loopholes in ACR Technologies
      • 3.3.2. Technological Challenges and Complexity of Devising Content Recognition Algorithms
    • 3.4. Market Trends
      • 3.4.1. Rise of Consumer Preferences
  • 4. Market Factor Analysis
    • 4.1. Porters Five Forces
    • 4.2. Supply/Value Chain
    • 4.3. PESTEL analysis
    • 4.4. Market Entropy
    • 4.5. Patent/Trademark Analysis
  • 5. Global Automatic Content Recognition, by Type, Application and Region (value and price ) (2017-2022)
    • 5.1. Introduction
    • 5.2. Global Automatic Content Recognition (Value)
      • 5.2.1. Global Automatic Content Recognition by: Type (Value)
        • 5.2.1.1. Acoustic & digital video fingerprinting
        • 5.2.1.2. Digital audio, video & image watermarking
        • 5.2.1.3. Optical character recognition
        • 5.2.1.4. Speech recognition
      • 5.2.2. Global Automatic Content Recognition by: Application (Value)
        • 5.2.2.1. Consumer Electronics
        • 5.2.2.2. E-commerce
        • 5.2.2.3. Education
        • 5.2.2.4. Automotive
        • 5.2.2.5. IT & telecommunication
        • 5.2.2.6. Healthcare
        • 5.2.2.7. Defense & public safety
        • 5.2.2.8. Avionics
        • 5.2.2.9. Others
      • 5.2.3. Global Automatic Content Recognition Region
        • 5.2.3.1. South America
          • 5.2.3.1.1. Brazil
          • 5.2.3.1.2. Argentina
          • 5.2.3.1.3. Rest of South America
        • 5.2.3.2. Asia Pacific
          • 5.2.3.2.1. China
          • 5.2.3.2.2. Japan
          • 5.2.3.2.3. India
          • 5.2.3.2.4. South Korea
          • 5.2.3.2.5. Taiwan
          • 5.2.3.2.6. Australia
          • 5.2.3.2.7. Rest of Asia-Pacific
        • 5.2.3.3. Europe
          • 5.2.3.3.1. Germany
          • 5.2.3.3.2. France
          • 5.2.3.3.3. Italy
          • 5.2.3.3.4. United Kingdom
          • 5.2.3.3.5. Netherlands
          • 5.2.3.3.6. Rest of Europe
        • 5.2.3.4. MEA
          • 5.2.3.4.1. Middle East
          • 5.2.3.4.2. Africa
        • 5.2.3.5. North America
          • 5.2.3.5.1. United States
          • 5.2.3.5.2. Canada
          • 5.2.3.5.3. Mexico
    • 5.3. Global Automatic Content Recognition (Price)
      • 5.3.1. Global Automatic Content Recognition by: Type (Price)
  • 6. Automatic Content Recognition: Manufacturers/Players Analysis
    • 6.1. Competitive Landscape
      • 6.1.1. Market Share Analysis
        • 6.1.1.1. Top 3
        • 6.1.1.2. Top 5
    • 6.2. Peer Group Analysis (2022)
    • 6.3. BCG Matrix
    • 6.4. Company Profile
      • 6.4.1. Arcsoft, Inc. (United States)
        • 6.4.1.1. Business Overview
        • 6.4.1.2. Products/Services Offerings
        • 6.4.1.3. Financial Analysis
        • 6.4.1.4. SWOT Analysis
      • 6.4.2. Google, Inc. (United States)
        • 6.4.2.1. Business Overview
        • 6.4.2.2. Products/Services Offerings
        • 6.4.2.3. Financial Analysis
        • 6.4.2.4. SWOT Analysis
      • 6.4.3. Microsoft Corporation (United States)
        • 6.4.3.1. Business Overview
        • 6.4.3.2. Products/Services Offerings
        • 6.4.3.3. Financial Analysis
        • 6.4.3.4. SWOT Analysis
      • 6.4.4. IPharro Media GmbH (Germany)
        • 6.4.4.1. Business Overview
        • 6.4.4.2. Products/Services Offerings
        • 6.4.4.3. Financial Analysis
        • 6.4.4.4. SWOT Analysis
      • 6.4.5. Digimarc Corporation (United States)
        • 6.4.5.1. Business Overview
        • 6.4.5.2. Products/Services Offerings
        • 6.4.5.3. Financial Analysis
        • 6.4.5.4. SWOT Analysis
      • 6.4.6. Nuance communications (United States)
        • 6.4.6.1. Business Overview
        • 6.4.6.2. Products/Services Offerings
        • 6.4.6.3. Financial Analysis
        • 6.4.6.4. SWOT Analysis
      • 6.4.7. Audible Magic Corporation (United States)
        • 6.4.7.1. Business Overview
        • 6.4.7.2. Products/Services Offerings
        • 6.4.7.3. Financial Analysis
        • 6.4.7.4. SWOT Analysis
      • 6.4.8. Civolution (United States)
        • 6.4.8.1. Business Overview
        • 6.4.8.2. Products/Services Offerings
        • 6.4.8.3. Financial Analysis
        • 6.4.8.4. SWOT Analysis
      • 6.4.9. Enswers, Inc. (South Korea)
        • 6.4.9.1. Business Overview
        • 6.4.9.2. Products/Services Offerings
        • 6.4.9.3. Financial Analysis
        • 6.4.9.4. SWOT Analysis
      • 6.4.10. Gracenote, Inc. (United States)
        • 6.4.10.1. Business Overview
        • 6.4.10.2. Products/Services Offerings
        • 6.4.10.3. Financial Analysis
        • 6.4.10.4. SWOT Analysis
      • 6.4.11. Mufin GmBH (Germany)
        • 6.4.11.1. Business Overview
        • 6.4.11.2. Products/Services Offerings
        • 6.4.11.3. Financial Analysis
        • 6.4.11.4. SWOT Analysis
      • 6.4.12. Shazam Entertainment Ltd. (United Kingdom)
        • 6.4.12.1. Business Overview
        • 6.4.12.2. Products/Services Offerings
        • 6.4.12.3. Financial Analysis
        • 6.4.12.4. SWOT Analysis
      • 6.4.13. Vobile, Inc. (United States)
        • 6.4.13.1. Business Overview
        • 6.4.13.2. Products/Services Offerings
        • 6.4.13.3. Financial Analysis
        • 6.4.13.4. SWOT Analysis
      • 6.4.14. Beatgrid Media BV (The Netherlands)
        • 6.4.14.1. Business Overview
        • 6.4.14.2. Products/Services Offerings
        • 6.4.14.3. Financial Analysis
        • 6.4.14.4. SWOT Analysis
      • 6.4.15. Clarifai, Inc. (United States)
        • 6.4.15.1. Business Overview
        • 6.4.15.2. Products/Services Offerings
        • 6.4.15.3. Financial Analysis
        • 6.4.15.4. SWOT Analysis
      • 6.4.16. VoiceBase, Inc. (United States)
        • 6.4.16.1. Business Overview
        • 6.4.16.2. Products/Services Offerings
        • 6.4.16.3. Financial Analysis
        • 6.4.16.4. SWOT Analysis
  • 7. Global Automatic Content Recognition Sale, by Type, Application and Region (value and price ) (2023-2028)
    • 7.1. Introduction
    • 7.2. Global Automatic Content Recognition (Value)
      • 7.2.1. Global Automatic Content Recognition by: Type (Value)
        • 7.2.1.1. Acoustic & digital video fingerprinting
        • 7.2.1.2. Digital audio, video & image watermarking
        • 7.2.1.3. Optical character recognition
        • 7.2.1.4. Speech recognition
      • 7.2.2. Global Automatic Content Recognition by: Application (Value)
        • 7.2.2.1. Consumer Electronics
        • 7.2.2.2. E-commerce
        • 7.2.2.3. Education
        • 7.2.2.4. Automotive
        • 7.2.2.5. IT & telecommunication
        • 7.2.2.6. Healthcare
        • 7.2.2.7. Defense & public safety
        • 7.2.2.8. Avionics
        • 7.2.2.9. Others
      • 7.2.3. Global Automatic Content Recognition Region
        • 7.2.3.1. South America
          • 7.2.3.1.1. Brazil
          • 7.2.3.1.2. Argentina
          • 7.2.3.1.3. Rest of South America
        • 7.2.3.2. Asia Pacific
          • 7.2.3.2.1. China
          • 7.2.3.2.2. Japan
          • 7.2.3.2.3. India
          • 7.2.3.2.4. South Korea
          • 7.2.3.2.5. Taiwan
          • 7.2.3.2.6. Australia
          • 7.2.3.2.7. Rest of Asia-Pacific
        • 7.2.3.3. Europe
          • 7.2.3.3.1. Germany
          • 7.2.3.3.2. France
          • 7.2.3.3.3. Italy
          • 7.2.3.3.4. United Kingdom
          • 7.2.3.3.5. Netherlands
          • 7.2.3.3.6. Rest of Europe
        • 7.2.3.4. MEA
          • 7.2.3.4.1. Middle East
          • 7.2.3.4.2. Africa
        • 7.2.3.5. North America
          • 7.2.3.5.1. United States
          • 7.2.3.5.2. Canada
          • 7.2.3.5.3. Mexico
    • 7.3. Global Automatic Content Recognition (Price)
      • 7.3.1. Global Automatic Content Recognition by: Type (Price)
  • 8. Appendix
    • 8.1. Acronyms
  • 9. Methodology and Data Source
    • 9.1. Methodology/Research Approach
      • 9.1.1. Research Programs/Design
      • 9.1.2. Market Size Estimation
      • 9.1.3. Market Breakdown and Data Triangulation
    • 9.2. Data Source
      • 9.2.1. Secondary Sources
      • 9.2.2. Primary Sources
    • 9.3. Disclaimer
List of Tables
  • Table 1. Automatic Content Recognition: by Type(USD Million)
  • Table 2. Automatic Content Recognition Acoustic & digital video fingerprinting , by Region USD Million (2017-2022)
  • Table 3. Automatic Content Recognition Digital audio, video & image watermarking , by Region USD Million (2017-2022)
  • Table 4. Automatic Content Recognition Optical character recognition , by Region USD Million (2017-2022)
  • Table 5. Automatic Content Recognition Speech recognition , by Region USD Million (2017-2022)
  • Table 6. Automatic Content Recognition: by Application(USD Million)
  • Table 7. Automatic Content Recognition Consumer Electronics , by Region USD Million (2017-2022)
  • Table 8. Automatic Content Recognition E-commerce , by Region USD Million (2017-2022)
  • Table 9. Automatic Content Recognition Education , by Region USD Million (2017-2022)
  • Table 10. Automatic Content Recognition Automotive , by Region USD Million (2017-2022)
  • Table 11. Automatic Content Recognition IT & telecommunication , by Region USD Million (2017-2022)
  • Table 12. Automatic Content Recognition Healthcare , by Region USD Million (2017-2022)
  • Table 13. Automatic Content Recognition Defense & public safety , by Region USD Million (2017-2022)
  • Table 14. Automatic Content Recognition Avionics , by Region USD Million (2017-2022)
  • Table 15. Automatic Content Recognition Others , by Region USD Million (2017-2022)
  • Table 16. South America Automatic Content Recognition, by Country USD Million (2017-2022)
  • Table 17. South America Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 18. South America Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 19. Brazil Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 20. Brazil Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 21. Argentina Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 22. Argentina Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 23. Rest of South America Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 24. Rest of South America Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 25. Asia Pacific Automatic Content Recognition, by Country USD Million (2017-2022)
  • Table 26. Asia Pacific Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 27. Asia Pacific Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 28. China Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 29. China Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 30. Japan Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 31. Japan Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 32. India Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 33. India Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 34. South Korea Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 35. South Korea Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 36. Taiwan Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 37. Taiwan Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 38. Australia Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 39. Australia Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 40. Rest of Asia-Pacific Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 41. Rest of Asia-Pacific Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 42. Europe Automatic Content Recognition, by Country USD Million (2017-2022)
  • Table 43. Europe Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 44. Europe Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 45. Germany Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 46. Germany Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 47. France Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 48. France Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 49. Italy Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 50. Italy Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 51. United Kingdom Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 52. United Kingdom Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 53. Netherlands Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 54. Netherlands Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 55. Rest of Europe Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 56. Rest of Europe Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 57. MEA Automatic Content Recognition, by Country USD Million (2017-2022)
  • Table 58. MEA Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 59. MEA Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 60. Middle East Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 61. Middle East Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 62. Africa Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 63. Africa Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 64. North America Automatic Content Recognition, by Country USD Million (2017-2022)
  • Table 65. North America Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 66. North America Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 67. United States Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 68. United States Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 69. Canada Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 70. Canada Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 71. Mexico Automatic Content Recognition, by Type USD Million (2017-2022)
  • Table 72. Mexico Automatic Content Recognition, by Application USD Million (2017-2022)
  • Table 73. Automatic Content Recognition: by Type(USD/Units)
  • Table 74. Company Basic Information, Sales Area and Its Competitors
  • Table 75. Company Basic Information, Sales Area and Its Competitors
  • Table 76. Company Basic Information, Sales Area and Its Competitors
  • Table 77. Company Basic Information, Sales Area and Its Competitors
  • Table 78. Company Basic Information, Sales Area and Its Competitors
  • Table 79. Company Basic Information, Sales Area and Its Competitors
  • Table 80. Company Basic Information, Sales Area and Its Competitors
  • Table 81. Company Basic Information, Sales Area and Its Competitors
  • Table 82. Company Basic Information, Sales Area and Its Competitors
  • Table 83. Company Basic Information, Sales Area and Its Competitors
  • Table 84. Company Basic Information, Sales Area and Its Competitors
  • Table 85. Company Basic Information, Sales Area and Its Competitors
  • Table 86. Company Basic Information, Sales Area and Its Competitors
  • Table 87. Company Basic Information, Sales Area and Its Competitors
  • Table 88. Company Basic Information, Sales Area and Its Competitors
  • Table 89. Company Basic Information, Sales Area and Its Competitors
  • Table 90. Automatic Content Recognition: by Type(USD Million)
  • Table 91. Automatic Content Recognition Acoustic & digital video fingerprinting , by Region USD Million (2023-2028)
  • Table 92. Automatic Content Recognition Digital audio, video & image watermarking , by Region USD Million (2023-2028)
  • Table 93. Automatic Content Recognition Optical character recognition , by Region USD Million (2023-2028)
  • Table 94. Automatic Content Recognition Speech recognition , by Region USD Million (2023-2028)
  • Table 95. Automatic Content Recognition: by Application(USD Million)
  • Table 96. Automatic Content Recognition Consumer Electronics , by Region USD Million (2023-2028)
  • Table 97. Automatic Content Recognition E-commerce , by Region USD Million (2023-2028)
  • Table 98. Automatic Content Recognition Education , by Region USD Million (2023-2028)
  • Table 99. Automatic Content Recognition Automotive , by Region USD Million (2023-2028)
  • Table 100. Automatic Content Recognition IT & telecommunication , by Region USD Million (2023-2028)
  • Table 101. Automatic Content Recognition Healthcare , by Region USD Million (2023-2028)
  • Table 102. Automatic Content Recognition Defense & public safety , by Region USD Million (2023-2028)
  • Table 103. Automatic Content Recognition Avionics , by Region USD Million (2023-2028)
  • Table 104. Automatic Content Recognition Others , by Region USD Million (2023-2028)
  • Table 105. South America Automatic Content Recognition, by Country USD Million (2023-2028)
  • Table 106. South America Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 107. South America Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 108. Brazil Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 109. Brazil Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 110. Argentina Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 111. Argentina Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 112. Rest of South America Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 113. Rest of South America Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 114. Asia Pacific Automatic Content Recognition, by Country USD Million (2023-2028)
  • Table 115. Asia Pacific Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 116. Asia Pacific Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 117. China Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 118. China Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 119. Japan Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 120. Japan Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 121. India Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 122. India Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 123. South Korea Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 124. South Korea Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 125. Taiwan Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 126. Taiwan Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 127. Australia Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 128. Australia Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 129. Rest of Asia-Pacific Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 130. Rest of Asia-Pacific Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 131. Europe Automatic Content Recognition, by Country USD Million (2023-2028)
  • Table 132. Europe Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 133. Europe Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 134. Germany Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 135. Germany Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 136. France Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 137. France Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 138. Italy Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 139. Italy Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 140. United Kingdom Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 141. United Kingdom Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 142. Netherlands Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 143. Netherlands Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 144. Rest of Europe Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 145. Rest of Europe Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 146. MEA Automatic Content Recognition, by Country USD Million (2023-2028)
  • Table 147. MEA Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 148. MEA Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 149. Middle East Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 150. Middle East Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 151. Africa Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 152. Africa Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 153. North America Automatic Content Recognition, by Country USD Million (2023-2028)
  • Table 154. North America Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 155. North America Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 156. United States Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 157. United States Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 158. Canada Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 159. Canada Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 160. Mexico Automatic Content Recognition, by Type USD Million (2023-2028)
  • Table 161. Mexico Automatic Content Recognition, by Application USD Million (2023-2028)
  • Table 162. Automatic Content Recognition: by Type(USD/Units)
  • Table 163. Research Programs/Design for This Report
  • Table 164. Key Data Information from Secondary Sources
  • Table 165. Key Data Information from Primary Sources
List of Figures
  • Figure 1. Porters Five Forces
  • Figure 2. Supply/Value Chain
  • Figure 3. PESTEL analysis
  • Figure 4. Global Automatic Content Recognition: by Type USD Million (2017-2022)
  • Figure 5. Global Automatic Content Recognition: by Application USD Million (2017-2022)
  • Figure 6. South America Automatic Content Recognition Share (%), by Country
  • Figure 7. Asia Pacific Automatic Content Recognition Share (%), by Country
  • Figure 8. Europe Automatic Content Recognition Share (%), by Country
  • Figure 9. MEA Automatic Content Recognition Share (%), by Country
  • Figure 10. North America Automatic Content Recognition Share (%), by Country
  • Figure 11. Global Automatic Content Recognition: by Type USD/Units (2017-2022)
  • Figure 12. Global Automatic Content Recognition share by Players 2022 (%)
  • Figure 13. Global Automatic Content Recognition share by Players (Top 3) 2022(%)
  • Figure 14. Global Automatic Content Recognition share by Players (Top 5) 2022(%)
  • Figure 15. BCG Matrix for key Companies
  • Figure 16. Arcsoft, Inc. (United States) Revenue, Net Income and Gross profit
  • Figure 17. Arcsoft, Inc. (United States) Revenue: by Geography 2022
  • Figure 18. Google, Inc. (United States) Revenue, Net Income and Gross profit
  • Figure 19. Google, Inc. (United States) Revenue: by Geography 2022
  • Figure 20. Microsoft Corporation (United States) Revenue, Net Income and Gross profit
  • Figure 21. Microsoft Corporation (United States) Revenue: by Geography 2022
  • Figure 22. IPharro Media GmbH (Germany) Revenue, Net Income and Gross profit
  • Figure 23. IPharro Media GmbH (Germany) Revenue: by Geography 2022
  • Figure 24. Digimarc Corporation (United States) Revenue, Net Income and Gross profit
  • Figure 25. Digimarc Corporation (United States) Revenue: by Geography 2022
  • Figure 26. Nuance communications (United States) Revenue, Net Income and Gross profit
  • Figure 27. Nuance communications (United States) Revenue: by Geography 2022
  • Figure 28. Audible Magic Corporation (United States) Revenue, Net Income and Gross profit
  • Figure 29. Audible Magic Corporation (United States) Revenue: by Geography 2022
  • Figure 30. Civolution (United States) Revenue, Net Income and Gross profit
  • Figure 31. Civolution (United States) Revenue: by Geography 2022
  • Figure 32. Enswers, Inc. (South Korea) Revenue, Net Income and Gross profit
  • Figure 33. Enswers, Inc. (South Korea) Revenue: by Geography 2022
  • Figure 34. Gracenote, Inc. (United States) Revenue, Net Income and Gross profit
  • Figure 35. Gracenote, Inc. (United States) Revenue: by Geography 2022
  • Figure 36. Mufin GmBH (Germany) Revenue, Net Income and Gross profit
  • Figure 37. Mufin GmBH (Germany) Revenue: by Geography 2022
  • Figure 38. Shazam Entertainment Ltd. (United Kingdom) Revenue, Net Income and Gross profit
  • Figure 39. Shazam Entertainment Ltd. (United Kingdom) Revenue: by Geography 2022
  • Figure 40. Vobile, Inc. (United States) Revenue, Net Income and Gross profit
  • Figure 41. Vobile, Inc. (United States) Revenue: by Geography 2022
  • Figure 42. Beatgrid Media BV (The Netherlands) Revenue, Net Income and Gross profit
  • Figure 43. Beatgrid Media BV (The Netherlands) Revenue: by Geography 2022
  • Figure 44. Clarifai, Inc. (United States) Revenue, Net Income and Gross profit
  • Figure 45. Clarifai, Inc. (United States) Revenue: by Geography 2022
  • Figure 46. VoiceBase, Inc. (United States) Revenue, Net Income and Gross profit
  • Figure 47. VoiceBase, Inc. (United States) Revenue: by Geography 2022
  • Figure 48. Global Automatic Content Recognition: by Type USD Million (2023-2028)
  • Figure 49. Global Automatic Content Recognition: by Application USD Million (2023-2028)
  • Figure 50. South America Automatic Content Recognition Share (%), by Country
  • Figure 51. Asia Pacific Automatic Content Recognition Share (%), by Country
  • Figure 52. Europe Automatic Content Recognition Share (%), by Country
  • Figure 53. MEA Automatic Content Recognition Share (%), by Country
  • Figure 54. North America Automatic Content Recognition Share (%), by Country
  • Figure 55. Global Automatic Content Recognition: by Type USD/Units (2023-2028)
List of companies from research coverage that are profiled in the study
  • Arcsoft, Inc. (United States)
  • Google, Inc. (United States)
  • Microsoft Corporation (United States)
  • iPharro Media GmbH (Germany)
  • Digimarc Corporation (United States)
  • Nuance communications (United States)
  • Audible Magic Corporation (United States)
  • Civolution (United States)
  • Enswers, Inc. (South Korea)
  • Gracenote, Inc. (United States)
  • Mufin GmBH (Germany)
  • Shazam Entertainment Ltd. (United Kingdom)
  • Vobile, Inc. (United States)
  • Beatgrid Media BV (The Netherlands)
  • Clarifai, Inc. (United States)
  • VoiceBase, Inc. (United States)
Additional players considered in the study are as follows:
ACRCloud (China) , DataScouting (Greece) , Viscovery Pte Ltd (Taiwan) , Voiceinteraction SA (Portugal)
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Key Highlights of Report


May 2023 228 Pages 63 Tables Base Year: 2022 Coverage: 15+ Companies; 18 Countries

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Global Automatic Content Recognition research Quantitative research analysis
Global Automatic Content Recognition research Qualitative Industry Analysis
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Frequently Asked Questions (FAQ):

Top performing companies in the Global Automatic Content Recognition market are Arcsoft, Inc. (United States), Google, Inc. (United States), Microsoft Corporation (United States), iPharro Media GmbH (Germany), Digimarc Corporation (United States), Nuance communications (United States), Audible Magic Corporation (United States), Civolution (United States), Enswers, Inc. (South Korea), Gracenote, Inc. (United States), Mufin GmBH (Germany), Shazam Entertainment Ltd. (United Kingdom), Vobile, Inc. (United States), Beatgrid Media BV (The Netherlands), Clarifai, Inc. (United States) and VoiceBase, Inc. (United States), to name a few.
"Rise of Consumer Preferences" is seen as one of major influencing trends for Automatic Content Recognition Market during projected period 2022-2028.
Acoustic & digital video fingerprinting segment in Global market to hold robust market share owing to "Increasing Integration of ACR in Smart TVs and Second Screen Devices Such as Smartphones and Wearables ".

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