View source for 17689299. METHOD AND APPARATUS WITH ABNORMAL CHANNEL OF MICROPHONE ARRAY DETECTION AND COMPENSATION SIGNAL GENERATION simplified abstract (Samsung Electronics Co., Ltd.)

=METHOD AND APPARATUS WITH ABNORMAL CHANNEL OF MICROPHONE ARRAY DETECTION AND COMPENSATION SIGNAL GENERATION=


==Organization Name==

[[:Category:Samsung Electronics Co., Ltd.|Samsung Electronics Co., Ltd.]]


[[Category:Samsung Electronics Co., Ltd.]]

==Inventor(s)==

[[:Category:Nam Soo Kim of Seoul (KR)|Nam Soo Kim of Seoul (KR)]][[Category:Nam Soo Kim of Seoul (KR)]]

[[:Category:Ji Won Yoon of Seoul (KR)|Ji Won Yoon of Seoul (KR)]][[Category:Ji Won Yoon of Seoul (KR)]]

==METHOD AND APPARATUS WITH ABNORMAL CHANNEL OF MICROPHONE ARRAY DETECTION AND COMPENSATION SIGNAL GENERATION - A simplified explanation of the abstract==


This abstract first appeared for US patent application 17689299 titled 'METHOD AND APPARATUS WITH ABNORMAL CHANNEL OF MICROPHONE ARRAY DETECTION AND COMPENSATION SIGNAL GENERATION

==Simplified Explanation==

The patent application describes a method for detecting abnormal channels in a microphone array using a neural network model. Here is a simplified explanation of the abstract:

* The method involves receiving sound signals from multiple channels of a microphone array.
* The sound signals are synchronized based on the spatial information of the microphone array.
* The synchronized sound signals and conditional information are inputted into a neural network model.
* The neural network model performs an inverse operation to detect any abnormal channels in the microphone array.

Potential Applications:

* Audio recording and processing systems
* Speech recognition systems
* Acoustic monitoring systems

Problems Solved:

* Identifying abnormal channels in a microphone array can be challenging.
* Manual inspection of each channel is time-consuming and prone to errors.
* Existing methods may not effectively detect abnormal channels.

Benefits:

* The method provides an automated and efficient way to detect abnormal channels.
* It improves the accuracy and reliability of sound source localization.
* It reduces the need for manual inspection and intervention.


==Original Abstract Submitted==

A method includes: receiving multi-channel sound source signals from a microphone array; synchronizing the multi-channel sound source signals based on spatial information of the microphone array; and detecting an abnormal channel of the microphone array by inputting the synchronized sound source signals and first conditional information to a neural network model configured to perform an inverse operation.



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