Voice intelligent classification method and system

A classification method and classification system technology, applied in speech analysis, speech recognition, instruments, etc., can solve problems such as slow convergence speed and poor classification effect, and achieve the effects of reducing parameters, speeding up convergence speed, and improving accuracy

Inactive Publication Date: 2018-12-25
HUBEI UNIV OF TECH
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Problems solved by technology

When the traditional cyclic neural network is applied to speech classification, it o

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Embodiment Construction

[0047] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0048] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0049] Such as figure 1 As shown, a voice intelligent classification method includes:

[0050] Step 101: Obtain the speech data of the training set.

[0051] Step 102: Process the speech data of the training set...

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Abstract

The invention discloses a voice intelligent classification method and system. The method includes: acquiring training set voice data; processing the training set voice data to obtain training set feature data; constructing an initialization model, wherein the initial classification model includes a first convolution layer, a first maximum pooling layer, a bidirectional cyclic neural network model,a second convolutional layer, a second maximum pooling layer, a first fully connected layer, a first dropout layer, a second fully connected layer, a second dropout layer, and a linear layer which are sequentially connected; training the initialization model by using the training set feature data to obtain a classification model; acquiring test set voice data; processing the test set voice data to obtain test set feature data; and classifying the test set feature data by using the classification mode. The method or system of the present invention can speed up the convergence speed in voice classification training, and can improve the judgment accuracy.

Description

technical field [0001] The invention relates to the field of speech classification, in particular to a speech intelligent classification method and system. Background technique [0002] With the development of deep learning technology, speech classification technology based on deep learning is gradually being applied to various fields. Since speech data is a kind of time series data, and recurrent neural network is suitable for time series data processing, recurrent neural network is the core of speech classification. Speech classification is to extract features from given speech data, and use the extracted features as the input data of the cyclic neural network to train the neural network to achieve the effect of judging the category of the speech. It is often used in speech recognition, speech emotion analysis, etc. aspect. The design of the recurrent neural network structure used in speech classification often directly affects the effect of speech classification. When ...

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Application Information

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IPC IPC(8): G10L15/16G10L15/06G10L25/30G10L25/24G10L25/63
CPCG10L15/063G10L15/16G10L25/24G10L25/30G10L25/63
Inventor 饶鉴熊展坤刘罡
Owner HUBEI UNIV OF TECH
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