17689744. PERCEPTUAL BASS EXTENSION WITH LOUDNESS MANAGEMENT AND ARTIFICIAL INTELLIGENCE (AI) simplified abstract (Samsung Electronics Co., Ltd.)

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PERCEPTUAL BASS EXTENSION WITH LOUDNESS MANAGEMENT AND ARTIFICIAL INTELLIGENCE (AI)

Organization Name

Samsung Electronics Co., Ltd.

Inventor(s)

Sunil Bharitkar of Stevenson Ranch CA (US)

William I. Saba of Santa Clarita CA (US)

PERCEPTUAL BASS EXTENSION WITH LOUDNESS MANAGEMENT AND ARTIFICIAL INTELLIGENCE (AI) - A simplified explanation of the abstract

This abstract first appeared for US patent application 17689744 titled 'PERCEPTUAL BASS EXTENSION WITH LOUDNESS MANAGEMENT AND ARTIFICIAL INTELLIGENCE (AI)

Simplified Explanation

The abstract describes a computer-implemented method for implementing a customizable compressor for sidechain processing associated with a loudspeaker. Machine learning is used to automatically adjust the parameters of the sidechain processing. The method also involves extracting channels, including a low-frequency effects (LFE) channel, for nonlinear signal synthesis. The LFE sidechain channel is mixed into a non-LFE sidechain using a proportional power-sum-based approach, while ensuring the LFE sidechain channel remains within a specified threshold of being level.

  • Computer-implemented method for customizable compressor for sidechain processing
  • Machine learning used to automatically tune sidechain processing parameters
  • Extraction of channels, including low-frequency effects (LFE) channel, for nonlinear signal synthesis
  • Proportional power-sum-based mix-in of LFE sidechain channel into non-LFE sidechain
  • Maintaining LFE sidechain channel within specified level threshold

Potential Applications

  • Audio processing and compression in loudspeaker systems
  • Sound engineering and production in music and film industries
  • Home theater systems and audio equipment

Problems Solved

  • Manual tuning of sidechain processing parameters can be time-consuming and subjective
  • Nonlinear signal synthesis can introduce distortion and imbalance without proper control
  • Maintaining the level of the LFE sidechain channel within a specified threshold can be challenging

Benefits

  • Customizable compressor allows for tailored sidechain processing in loudspeaker systems
  • Machine learning automates parameter tuning, saving time and improving accuracy
  • Proportional power-sum-based mix-in ensures balanced and controlled nonlinear signal synthesis
  • Maintaining LFE sidechain channel within specified level threshold improves audio quality and avoids distortion.


Original Abstract Submitted

One embodiment provides a computer-implemented method that includes implementing a customizable compressor for at least one sidechain processing associated with a loudspeaker. Machine learning is applied to automatically tune one or more parameters of the at least one sidechain processing. One or more channels are extracted, including a low-frequency effects (LFE) channel, for nonlinear signal synthesis. A proportional power-sum-based mix-in of an LFE sidechain channel is applied into a non-LFE sidechain. The LFE sidechain channel is maintained within a specified threshold of being level, before and after nonlinear signal synthesis.

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