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DIFF Subgroup
G10L 19/20

using sound class specific coding, hybrid encoders or object based coding

Introduced: January 2013

Full Title

Full titles differ between systems:

IPC:

Speech or audio signal analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis > using predictive techniques > Vocoder architecture > Vocoders using multiple modes > using sound class specific coding, hybrid encoders or object based coding

CPC:

Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis (in musical instruments G10H) > using predictive techniques > Vocoder architecture > Vocoders using multiple modes > using sound class specific coding, hybrid encoders or object based coding

No child classifications to compare. This is a leaf node in both IPC and CPC.

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