Voice extraction method under high background noise

A technology for background noise and speech extraction, applied in speech analysis, instruments, etc., can solve the problems of limiting the ability to adapt to noise environments, lack of effective methods for step size factors, etc., to achieve the effect of improving fitness

Inactive Publication Date: 2014-03-05
CHENGDU MILITARY GENERAL HOSPITAL OF PLA
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Problems solved by technology

A typical example is "Northwestern Polytechnical University. A speech noise reduction method based on wavelet transform and variable step size least mean square algorithm. Chinese invention patent, CN101894561A, 2010.11.24" disclosed speech noise reduction method, which makes full use of wavelet Transformation has advanta

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  • Voice extraction method under high background noise
  • Voice extraction method under high background noise
  • Voice extraction method under high background noise

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Embodiment

[0027] figure 1 It is a flow chart of a specific embodiment of the speech extraction method under strong background noise of the present invention. Such as figure 1 Shown, the speech extraction method under the strong background noise of the present invention, comprises the following steps:

[0028] S101: Preprocessing:

[0029] Preprocess the original speech signal with strong background noise, including discrete sampling and quantization, and extract P data frames f composed of M sampling points p (t m ), where p=0,1,...,P represents the frame number where the data is located, and m=0,1,...,M represents the sample number.

[0030] The audio sampling hardware system of this embodiment adopts the digital codec chip WM8978 produced by Wolfson Microelectronics to collect the original speech signal with background noise input by the microphone sensor. The chip has built-in I2S bus support, and the Cortex- M4 series processors are connected to STM32F303; STM32F3 series proces...

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Abstract

The invention discloses a voice extraction method under high background noise. At first, original voice signals containing the high background noise are discretely sampled in advance and quantized to obtain data frames, a wavelet neural network based on a Morlet wavelet function is constructed for the data frames, a particle swarm fitness function is constructed for parameters of the wavelet neural network, then the optimal parameter is obtained through a particle swarm algorithm, the data frames are input to the wavelet neural network to be filtered, and therefore the noise is removed, and voice signals are extracted. The parameters of the wavelet neural network are obtained by means of the particle swarm algorithm. Therefore, fitness for different environmental noise characteristics can be improved through the method.

Description

technical field [0001] The invention belongs to the technical field of speech extraction, and more specifically relates to a speech extraction method under strong background noise. Background technique [0002] In some occasions with strong background noise, such as beside the highway, in roaring vehicles, among noisy crowds, etc., how to eliminate the strong background noise and effectively extract the user's voice is the speech recognition device in these special occasions. One of the main problems. [0003] At present, the noise reduction technologies mainly used in various voice communication devices include: [0004] 1) Model-based noise reduction methods, typically such as the speech model and Noise model, which filters and compensates the received audio signal by setting adaptation rules. This method has a good denoising effect in the case of a high degree of adaptation, but requires more prior knowledge to pre-build user speech and noise models. [0005] 2) Activ...

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Application Information

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IPC IPC(8): G10L21/0208
Inventor 周龙甫呼永河张超群李正郝大鹏赵明
Owner CHENGDU MILITARY GENERAL HOSPITAL OF PLA
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