A Noise Classification Method Based on bp Network

A BP network and noise classification technology, applied in speech analysis, instruments, etc., can solve the problem of low classification accuracy, and achieve the effect of high noise classification accuracy, strong experimentability, and wide applicability

Active Publication Date: 2022-04-05
TIANJIN UNIV
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Problems solved by technology

[0004] However, the noise classification methods proposed so far have low classification accuracy.

Method used

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  • A Noise Classification Method Based on bp Network
  • A Noise Classification Method Based on bp Network
  • A Noise Classification Method Based on bp Network

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[0074] (1) Preprocessing the input noise signal:

[0075] 1. Select data:

[0076] Select Pink, Factory1, F16, Destoryerengine, Buccaneer1; Babble, White, Hfchannel, Factory2, Buccaneer2; Volvo, Machinegun, M109, Leopard, Destoryerops as samples from the Noisex-92 standard noise library, and the sampling frequency is 16KHz. It is divided into three categories as the basis for the classification of the first-level BP network, namely: A1 category: Pink, Factory1, F16, Destoryerengine, Buccaneer1; A2 category: Babble, White, Hfchannel, Factory2, Buccaneer2; A3 category: Volvo, Machinegun , M109, Leopard, Destoryerops.

[0077] 2. Framing and windowing

[0078] (1) Framing: the frame length is 256 points, and the frame shift is 128 points;

[0079] (2) The window function is a Hamming window;

[0080] (2) After preprocessing, there are 36,713 frames of data for each type of noise, and 550,695 frames of data for 15 types of noise. Perform Fourier transform on each frame of dat...

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Abstract

A noise classification method based on BP network: preprocess the input noise signal; perform Fourier transform on each preprocessed noise signal to obtain the noise signal power spectrum; use the noise signal power spectrum of each frame to separate Calculate the Mel frequency cepstral coefficient of each frame noise signal and the first-order difference of the Mel frequency cepstral coefficient; calculate the gamma pass frequency cepstral coefficient of each frame noise signal; the Mel frequency of each frame noise signal The cepstral coefficient, the first-order difference of the Mel frequency cepstral coefficient and the Gamma-pass frequency cepstral coefficient are combined as the joint feature of the frame noise signal, and part of the joint feature of all frame noise signals is used as the training data, and the other part is used as the training data. Test data; train the first-level BP network and the second-level BP network respectively; jointly test the first-level BP network and the second-level BP network, and obtain the final noise signal classification result. The present invention has higher noise classification accuracy.

Description

technical field [0001] The invention relates to a noise classification method. In particular, it relates to a noise classification method based on BP network. Background technique [0002] In the process of speech signal processing, the problem of noise pollution is unavoidable. With the wide application of digital voice signals in scientific research and daily life, the impact of noise on digital voice signals has become more and more obvious. How to effectively suppress noise and improve the quality and intelligibility of voice signals has become a hot topic for many scholars. In speech enhancement technology, a major research difficulty is that there are many sources of noise. The statistical characteristics of different noises are not the same. Therefore, in practical applications, in order to achieve better signal processing effects, it is necessary to treat noises with different noise characteristics differently according to the application. [0003] Generally speak...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G10L21/0208G10L21/0216G10L25/24G10L25/27G10L25/30
CPCG10L21/0208G10L21/0216G10L25/27G10L25/24G10L25/30
Inventor 张涛耿彦章邵洋洋
Owner TIANJIN UNIV
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