US 12,294,839 B2
Method and system for repetitive noise identification
Pui Ho Lam, Hong Kong (HK); Tze Yui Ho, Hong Kong (HK); Man Tik Li, Hong Kong (HK); Jingyi Xu, Hong Kong (HK); and Wai Cheong Ku, Hong Kong (HK)
Assigned to Hong Kong Applied Science and Technology Research Institute Company Limited, Shatin (HK)
Filed by Hong Kong Applied Science and Technology Research Institute Company Limited, Hong Kong (HK)
Filed on May 5, 2023, as Appl. No. 18/144,017.
Claims priority of provisional application 63/338,901, filed on May 6, 2022.
Prior Publication US 2023/0362539 A1, Nov. 9, 2023
Int. Cl. H04R 29/00 (2006.01); G06N 3/08 (2023.01); H04R 3/00 (2006.01); G10K 11/16 (2006.01)
CPC H04R 3/00 (2013.01) [G06N 3/08 (2013.01); H04R 2420/07 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A repetitive noise identification method comprising the steps of:
obtaining a set of ambient sound data;
obtaining a set of sample target noises containing at least one sample target noise;
creating a set of cyclically-shifted target noises by cyclically shifting each of the sample target noises by one or more time-shift intervals;
creating a set of training target noises comprising the set of sample target noises and the set of cyclically-shifted target noises;
training a convoluted neural network to identify one or more target noises using the set of training target noises and the set of ambient sound data;
implementing the convoluted neural network in a monitoring device, the monitoring device having a microphone, a processing unit, a storage unit storing the convoluted neural network, and a wireless communications unit;
deploying the monitoring unit in an area to be monitored for the target sounds;
obtaining an ambient noise sample having an interval time length TA with the microphone;
analyzing the ambient noise sample with the processing unit to determine whether the ambient noise sample includes any of the target noises and if so, sending a data signal containing alert data to a concentrator, otherwise returning to the previous step;
sending the data signal to a cloud-based platform from the monitoring device;
sending the data signal from the cloud-based platform to a backend server;
storing the alert data in a database; and
publishing the alert data to one or more users through one or more access devices.