Typical abnormal sound detection method and device

An abnormal sound and typical technology, applied in speech analysis, instruments, etc., can solve the problems that are not easy to apply in the field of video and audio monitoring, and the implementation process is complicated, so as to achieve the effect of expanding the scope of use and low computational complexity

Inactive Publication Date: 2016-07-27
ZHEJIANG DAHUA TECH
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Although this method can consider the influence of background noise, the implementation process

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  • Typical abnormal sound detection method and device
  • Typical abnormal sound detection method and device
  • Typical abnormal sound detection method and device

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[0022] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0023] The embodiment of the present invention provides a method for detecting abnormal sounds based on the characteristics of the spectrogram. For sound information, people rely on the three characteristics of timbre, pitch, and volume to distinguish, and these characteristics can be characterized by the parameters in the time-frequency structure of the spectrogram. The spectrogram is a three-dimensional perceptual diagram describing the...

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Abstract

The invention discloses a typical abnormal sound detection method and a device, relates to the voice signal processing field and particularly provides an abnormal sound detection method based on spectrograms. According to the method, a sound signal is acquired, the sound signal is pre-processed, and effective signal segments of the sound signal are determined; the spectrograms of the effective signal segments are acquired, a to-be-tested identification characteristic matrix is determined, and the to-be-tested identification characteristic matrix is used for representing sound intensity distribution of the sound signal on the time-frequency domain; similarities between the to-be-tested identification characteristic matrix and each standard identification characteristic matrix in an abnormal sound model database are calculated, and abnormal sound types of the effective signal segments are determined according to calculation results; computational complexity in an abnormal sound identification process is simplified, and detection accuracy is improved.

Description

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Owner ZHEJIANG DAHUA TECH
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