Noise reduction and abnormal sound detection method applied to rail transit
An abnormal sound, rail transit technology, applied in speech analysis, speech recognition, instruments, etc., can solve the problem that audio monitoring is difficult to achieve auditory effect, and achieve the effect of improving audio monitoring effect, suppressing noise components, and improving response speed.
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[0027] A noise reduction and abnormal sound detection method applied to rail transit proposed by the present invention will be described in detail below with reference to the drawings and embodiments.
[0028] Such as figure 1 , 2 Shown is the method flowchart of the embodiment of the present invention, and the method includes the following steps:
[0029] S0, generate a certain number of sound signal sample libraries within the scope of the rail transit monitoring area, then extract the eigenvalues of each sound signal in the sample library, form a eigenvector according to the eigenvalues of each sound signal, and then process the formed eigenvectors Perform clustering operations to generate sample library feature models. The clustering operation specifically includes: modeling using a Gaussian Mixture Model (GMM), or modeling using other models, such as a Hidden Markov Model (HMM);
[0030] S1, collecting sound signals within the scope of the rail traffic monitoring a...
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