Variation-limited Boltzmann machine based denoising audio feature extraction algorithm
A technology of limited Boltzmann machine and noisy Boltzmann machine, applied in the field of denoising frequency feature extraction algorithm, can solve problems such as time-consuming, and achieve the effect of simple theory
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[0055] The present invention will be further described below in conjunction with the drawings and embodiments.
[0056] Such as Figure 1-2 As shown, a classification method based on audio feature signals, the specific steps are as follows:
[0057] (1) Audio signal collection: Collect audio signals to obtain audio samples.
[0058] (2) Signal preprocessing: group the collected audio signals into training combination test groups.
[0059] (3) The construction of the restricted denoising Boltzmann machine model: the excellent unsupervised learning ability of the restricted Boltzmann machine is used to construct a learning model. The model is divided into a visible layer, a hidden layer and a label layer.
[0060] (4) Denoising frequency feature model training: First, use the probability of audio features to appear greater than the probability of noise features to realize the hidden layer of the pretrained restricted denoising Boltzmann machine model is divided into two groups, and then ...
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