18147777. MICROPHONE CHANNEL SELF-NOISE SILENCING simplified abstract (Intel Corporation)
Contents
MICROPHONE CHANNEL SELF-NOISE SILENCING
Organization Name
Inventor(s)
Adam Kupryjanow of Gdansk (PL)
Przemyslaw Maziewski of Gdansk (PL)
Lukasz Pindor of Pruszcz Gdanski (PL)
Sebastian Rosenkiewicz of Gdansk (PL)
MICROPHONE CHANNEL SELF-NOISE SILENCING - A simplified explanation of the abstract
This abstract first appeared for US patent application 18147777 titled 'MICROPHONE CHANNEL SELF-NOISE SILENCING
Simplified Explanation: This patent application describes a user computing device with a microphone that uses a self-noise silencer to remove background noise from audio signals.
- The device generates a feature set based on the audio signal, identifying magnitude values for different frequency components.
- A machine learning model is trained to identify frequencies contributing to self-noise at the microphone.
- An attenuation mask is created based on the model's output, which specifies how much to reduce the magnitude values of certain frequency components.
- The attenuation mask is applied to the magnitude values to eliminate self-noise and produce a cleaner audio signal.
Key Features and Innovation:
- Utilizes a self-noise silencer to remove background noise from audio signals.
- Incorporates machine learning to identify and reduce frequencies contributing to self-noise.
- Generates an attenuation mask to selectively reduce the magnitude values of specific frequency components.
Potential Applications:
- Enhancing audio quality in voice recognition systems.
- Improving audio recordings in noisy environments.
- Enhancing the performance of speech recognition software.
Problems Solved:
- Eliminates self-noise from audio signals.
- Improves the accuracy of audio processing systems.
- Enhances the overall quality of audio recordings.
Benefits:
- Cleaner and clearer audio signals.
- Improved performance of audio-based applications.
- Enhanced user experience with voice-controlled devices.
Commercial Applications:
- This technology can be utilized in smartphones, smart speakers, and other voice-activated devices to enhance audio quality and user experience.
Questions about Self-Noise Silencer Technology: 1. How does the self-noise silencer technology impact the performance of voice recognition systems? 2. What are the potential applications of this technology in the field of audio processing?
Frequently Updated Research: Ongoing research in machine learning algorithms for noise reduction in audio signals may further improve the efficiency and accuracy of self-noise silencer technology.
Original Abstract Submitted
A user computing device includes a microphone to generate an audio signal and a self-noise silencer to generate a feature set corresponding to the audio signal, where the input feature identifies, for each of a plurality of frequency components in the audio signal, a respective magnitude value. At least a portion of the feature set is provided as an input to a machine learning model trained to infer frequencies contributing to self-noise generated at the microphone. An attenuation mask is generated, based on an output of the machine learning model, that identifies an attenuation value for at least a subset of the plurality of frequency components. The attenuation mask is applied to at least the subset of the magnitude values of the plurality of frequency components to remove self-noise from the audio signal and generate a denoised version of the audio signal.
