QUALCOMM Incorporated (20240331679). MACHINE LEARNING-BASED FEEDBACK CANCELLATION simplified abstract
Contents
MACHINE LEARNING-BASED FEEDBACK CANCELLATION
Organization Name
Inventor(s)
Vahid Montazeri of Newport Beach CA (US)
Rogerio Guedes Alves of Macomb Township MI (US)
Jacob Jon Bean of Vista CA (US)
Erik Visser of San Diego CA (US)
MACHINE LEARNING-BASED FEEDBACK CANCELLATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240331679 titled 'MACHINE LEARNING-BASED FEEDBACK CANCELLATION
Simplified Explanation: This patent application describes a method for processing audio signals in a personal audio amplification system to cancel feedback using machine learning.
- The method involves receiving an input audio signal containing both desired audio and feedback components.
- A machine learning model is applied to the input signal to determine an output audio signal with reduced feedback.
- The system aims to improve audio quality by eliminating unwanted feedback noise.
Key Features and Innovation:
- Utilizes machine learning to cancel feedback in audio signals.
- Enhances audio quality in personal audio amplification systems.
- Provides a more efficient and effective method for feedback cancellation.
Potential Applications:
- Personal audio devices
- Hearing aids
- Public address systems
Problems Solved:
- Feedback noise in audio signals
- Improved audio quality in personal amplification systems
Benefits:
- Enhanced listening experience
- Clearer audio output
- Reduction of unwanted noise
Commercial Applications: The technology can be applied in various commercial settings such as audio equipment manufacturing, entertainment venues, and healthcare facilities for hearing aid devices.
Prior Art: Readers can explore prior art related to audio signal processing, machine learning in audio technology, and feedback cancellation methods in personal amplification systems.
Frequently Updated Research: Stay informed about advancements in machine learning algorithms for audio signal processing, feedback cancellation techniques, and innovations in personal audio amplification systems.
Questions about Audio Signal Processing: 1. How does machine learning improve feedback cancellation in audio signals? 2. What are the potential challenges in implementing this technology in personal audio devices?
Original Abstract Submitted
this disclosure provides systems, methods, and devices for audio signal processing that support feedback cancellation in a personal audio amplification system. in a first aspect, a method of signal processing includes receiving an input audio signal, wherein the input audio signal includes a desired audio component and a feedback component; and reducing the feedback component by applying a machine learning model to the input audio signal to determine an output audio signal. other aspects and features are also claimed and described.
