Speech emotion recognition method based on multistage residual convolutional neural network

A technology of convolutional neural network and speech emotion recognition, which is applied in speech recognition, biological neural network model, speech analysis, etc., can solve the problems such as the decline of recognition rate and the loss of original signal features, and achieve the goal of reducing the loss rate and improving the recognition rate Effect

Active Publication Date: 2020-07-17
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

However, the CNN model has the problem that with the deepening of the convolutional layer, the features of the original signal are gradually lost, which leads to a decrease in the recognition rate.

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  • Speech emotion recognition method based on multistage residual convolutional neural network
  • Speech emotion recognition method based on multistage residual convolutional neural network
  • Speech emotion recognition method based on multistage residual convolutional neural network

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Embodiment Construction

[0038] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic concept of the present invention, and the following embodiments and the features in the embodiments can be combined with each other in the case of no conflict.

[0039] see Figure 1 ~ Figure 3 , figure 1 It is a speech emotion recognition method based on a multi-level residual convolutional neural network, comprisin...

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Abstract

The invention relates to a speech emotion recognition method based on a multistage residual convolutional neural network, and belongs to the technical field of speech signal analysis, image processingand the like. The method comprises the following steps: 1) a training process: collecting and preprocessing sound signals with all emotions to generate a spectrogram; constructing a multi-stage residual convolutional neural network, and inputting the spectrogram into the multi-stage residual convolutional neural network for training; 2) a test process: acquiring and preprocessing a to-be-identified sound signal, and generating a to-be-identified spectrogram; and then inputting the to-be-identified spectrogram into the trained multistage residual convolutional neural network to obtain a recognition result. According to the method, the CNN is subjected to feature compensation by crossing multi-stage residual blocks, so that the problem of feature loss of the CNN along with deepening of a convolution layer is solved, and the recognition rate is increased.

Description

technical field [0001] The invention belongs to the technical fields of voice signal analysis and image processing, and relates to a voice emotion recognition method based on a multi-level residual convolutional neural network. Background technique [0002] With the development of deep learning technology, there are more and more researches on the combination of speech emotion recognition technology and deep learning technology, and using convolutional neural network (CNN) as the recognition model is one of the research focuses. CNN's convolution kernel can extract features at different levels, and can complete the entire process of feature extraction and model recognition, thereby omitting the cumbersome and complicated manual feature engineering process. However, the CNN model has the problem that with the deepening of the convolutional layer, the characteristics of the original signal are gradually lost, resulting in a decrease in the recognition rate. Contents of the i...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G10L25/63G10L25/18G10L15/06G06N3/04
CPCG10L25/63G10L25/18G10L15/063G06N3/045
Inventor 郑凯夏志广张毅
Owner CHONGQING UNIV OF POSTS & TELECOMM
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