Short-wave channel speech anti-fading auxiliary enhancement method based on convolutional neural network

A convolutional neural network and short-wave channel technology, which is applied in the field of speech enhancement assistance against short-wave fading, can solve the problems of limited improvement of single-channel received speech signals and less research on single-channel received speech signal enhancement processing.

Active Publication Date: 2021-04-09
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

There are few studies on the enhancement processing of single-channel received speech signals, and the existing speech

Method used

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  • Short-wave channel speech anti-fading auxiliary enhancement method based on convolutional neural network
  • Short-wave channel speech anti-fading auxiliary enhancement method based on convolutional neural network
  • Short-wave channel speech anti-fading auxiliary enhancement method based on convolutional neural network

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specific Embodiment

[0034] A specific embodiment includes the following steps:

[0035] Step 1: Take the above TIMIT speech data set x train Constructing shortwave speech data set with channel fading and the noisy speech dataset

[0036]

[0037]

[0038] where n train Additive noise for the specified signal-to-noise ratio, "*" means convolution. Thus, 9,000 pieces of short-wave speech with channel fading with a total duration of about 10 hours were obtained and noisy speech Shortwave Speech Dataset and the noisy speech dataset Feature extraction is performed through Short time Fourier transform (STFT). Shortwave Speech Signal Amplitude Spectrum Dataset Obtained by Feature Extraction As an input signal, a noisy speech signal magnitude spectrum dataset As the target, use the adam optimizer to train the convolutional neural network model with a learning rate of 1e-5, the number of training epochs is fixed at 45, and the mean square error (MSE) is used as the objective functio...

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Abstract

The invention discloses a short-wave channel speech anti-fading auxiliary enhancement method based on a convolutional neural network, belongs to the technical field of communication, and particularly relates to a short-wave fading resistant speech enhancement auxiliary method. Firstly, an applicable short-wave speech communication model is defined; after a transmitting terminal obtains a speech signal sample, background environment noise is eliminated by using an existing speech enhancement technology, then SSB modulation is carried out, up-conversion is carried out to a short-wave frequency band for transmission, a transmitting signal reaches a receiver at a far end through a short-wave channel, and speech enhancement is carried out on the received signal after down-conversion and SSB demodulation, so that the purpose of the invention is achieved. The anti-fading convolutional neural network can be used for assisting most speech enhancement algorithms based on speech feature extraction and further improving the quality of short-wave received speech signals, for example, the anti-fading convolutional neural network can be combined with a spectral subtraction method, a method based on a statistical model, an NMF algorithm and the like described in the background technology.

Description

technical field [0001] The invention belongs to the technical field of communication, in particular to a speech enhancement auxiliary method for resisting short-wave fading. Background technique [0002] Wireless shortwave channel voice communication is a common means of communication, widely used in emergency communication, military communication and radio communication. Long-distance wireless communication can be carried out at a lower cost through the ionospheric short-wave channel, so short-wave communication has the characteristics of low cost and high flexibility. However, due to the low bandwidth of the short-wave channel, voice signals are usually sent in the form of analog signals after being modulated by analog single-sideband (SSB). The short-wave channel has the characteristics of rapid change, frequency selectivity, and large-scale energy loss after the signal is transmitted over a long distance. The quality of the received short-wave voice signal is often poor...

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Application Information

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IPC IPC(8): G10L21/0216G10L25/30
CPCG10L21/0216G10L25/30
Inventor 陈延涛董彬虹张晓雪蔡沅沅李昊
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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