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DIFF Subgroup Additional Only
G10H 2250/311

Neural networks for electrophonic musical instruments or musical processing, e.g. for musical recognition or control, automatic composition or improvisation

Full Title

Aspects of algorithms or signal processing methods without intrinsic musical character, yet specifically adapted for or used in electrophonic musical processing > Neural networks for electrophonic musical instruments or musical processing, e.g. for musical recognition or control, automatic composition or improvisation

Top Applicants

Top Applicants (IPC)

Class G10,2013–2023, worldwide · Source: EPO PATSTAT

  1. SAMSUNG ELECTRONICS COMPANY KR 5,218
  2. GOOGLE US 4,644
  3. FRAUNHOFER DE 4,601
  4. SONY CORPORATION JP 2,380
  5. HUAWEI TECHNOLOGIES COMPANY CN 2,179
  6. YAMAHA CORPORATION 2,120
  7. IBM (INTERNATIONAL BUSINESS MACHINES CORPORATION) US 1,974
  8. MICROSOFT TECHNOLOGY LICENSING US 1,916
  9. AMAZON TECHNOLOGIES US 1,866
  10. DOLBY LABORATORIES LICENSING CORPORATION US 1,843

Top Applicants (CPC)

Class G10,2013–2023, worldwide · Source: EPO PATSTAT

  1. SAMSUNG ELECTRONICS COMPANY KR 6,277
  2. GOOGLE US 5,429
  3. FRAUNHOFER DE 4,984
  4. SONY CORPORATION JP 2,808
  5. HUAWEI TECHNOLOGIES COMPANY CN 2,577
  6. MICROSOFT TECHNOLOGY LICENSING US 2,382
  7. DOLBY LABORATORIES LICENSING CORPORATION US 2,123
  8. QUALCOMM US 2,117
  9. IBM (INTERNATIONAL BUSINESS MACHINES CORPORATION) US 2,049
  10. AMAZON TECHNOLOGIES US 1,924