Patent Document ID: 10014003
Application ID: 15041487
Patent Flag: 1

Claim One:
1. A method implemented on an audio signal monitoring system for detecting a particular abnormal sound in an environment with mixed background noise, the method comprising: acquiring a sound signal via a microphone; converting, by a converter, the acquired sound signal into time-frequency domain signals; separating abnormal sounds from the converted sound signals; extracting Mel-frequency cepstral coefficient (MFCC) parameters according to the separated abnormal sounds; calculating hidden Markov model (HMM) likelihoods according to the separated abnormal sounds; and comparing the HMM likelihoods of the separated abnormal sounds with a reference value to determine whether or not an abnormal sound has occurred; wherein the separating abnormal sounds comprises decomposing the converted sound signals into a linear combination of several vectors through a background noise base and a plurality of abnormal sound bases and determining degrees of similarity to a pre-trained abnormal sound signal, wherein calculating hidden Markov model (HMM) likelihoods according to the separated abnormal sounds comprises: detecting a highest likelihood of each separated abnormal sound by an HMM of the background noise and an HMM of the separated abnormal sound after the extracting of the MFCC parameters according to the separated abnormal sounds through non-negative matrix factorization (NMF), wherein the background noise base and the abnormal sound bases are trained and saved before detecting the particular abnormal sound, and wherein a verification based on the HMM likelihoods is performed only for the separated abnormal sounds through the separating of the abnormal sounds based on the NMF.