A Distributed Speech Enhancement Method Based on Distributed Consensus and MVDR Beamforming

A speech enhancement and distributed technology, applied in speech analysis, instruments, etc., can solve problems such as tree topology generation troubles

Active Publication Date: 2018-05-15
DALIAN UNIV OF TECH
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Problems solved by technology

This algorithm improves the shortcomings of network topology limitations existing in techniques 1 and 2. Node transmission is much faster than network direct transmission, but the disadvantage is that tree topology generation is more troublesome. It is necessary to know the network structure in advance and perform preprocessing

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  • A Distributed Speech Enhancement Method Based on Distributed Consensus and MVDR Beamforming
  • A Distributed Speech Enhancement Method Based on Distributed Consensus and MVDR Beamforming
  • A Distributed Speech Enhancement Method Based on Distributed Consensus and MVDR Beamforming

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[0071] In order to make the technical solutions and advantages of the present invention more clear, the technical solutions in the embodiments of the present invention are clearly and completely described below in conjunction with the drawings in the embodiments of the present invention:

[0072] Such as figure 1 A distributed voice enhancement method based on distributed consistency and MVDR is shown, which specifically includes the following steps:

[0073] S1: Use the improved random acoustic sensor network generation algorithm to generate the coordinates of the sensor network nodes, and calculate the connection matrix of the nodes, the degree of the nodes and the set of adjacent nodes of the nodes.

[0074] The random acoustic sensor network generation algorithm is mainly based on the Salama model that can control the average node degree of the random network [5] network random generation algorithm. Let there be a random acoustic sensor network node set G={g with N nodes...

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Abstract

The invention discloses a distributed speech enhancement method based on distributed consistency and MVDR beamforming, which includes the following steps: S1: using an improved random acoustic sensor network generation algorithm to generate the coordinates of the sensor network nodes, and calculating the connection matrix of the nodes, The degree of the node and the set of adjacent nodes of the node; S2: use the sensor network generated in S1 to receive the noisy speech signal, and perform MVDR preprocessing on the noisy speech signal received by each node to obtain the speech preprocessing matrix (0) and noise preprocessing Matrix (0); S3: use the connection matrix of nodes obtained from S1, the degree of nodes and the set of adjacent nodes of nodes and S2 to obtain the speech preprocessing matrix (0) and noise preprocessing matrix (0) for distributed consistency iteration , so that each node can obtain a consistent speech signal zi(t) in the MVDR speech enhancement time domain.

Description

technical field [0001] The invention relates to the technical field of speech signal processing, in particular to a distributed speech enhancement method based on distributed consistency and MVDR. Background technique [0002] Speech signal processing is one of the core technologies in the fields of modern communication, multimedia applications and artificial intelligence. During the voice collection process, due to environmental noise, room reverberation, etc., the sound quality and clarity of the acquired voice will decrease. Speech enhancement, as a pre-processing scheme, is an effective way to suppress interference. [0003] In the information age, the most important and basic technology for information acquisition - sensor technology, has also been greatly developed. Wireless Sensor Networks (WSN, Wireless SensorNetworks) with perception capabilities, computing capabilities and communication capabilities are also proposed. Wireless sensor network integrates sensor te...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G10L21/0216G10L25/21
Inventor 陈喆殷福亮李达
Owner DALIAN UNIV OF TECH
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