Speech classification method based on deep neural network

A deep neural network and classification method technology, applied in neural learning methods, biological neural network models, speech analysis, etc.

Active Publication Date: 2018-05-08
SICHUAN UNIV
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Problems solved by technology

[0005] The present invention provides a speech classification method based on a deep neural network in view of the above deficiencies, and solves the proble...

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  • Speech classification method based on deep neural network
  • Speech classification method based on deep neural network
  • Speech classification method based on deep neural network

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[0058] specific implementation plan

[0059] The technical solutions in this embodiment will be described in detail below in conjunction with the various drawings in the embodiments of the present invention; however, the embodiments described here are only part of the embodiments of the present invention, not all implementations of the description. example.

[0060] see figure 1 , a core model of speech classification based on a deep neural network is a deep neural network model composed of multiple convolutional blocks using an attention mechanism. One is the convolutional neural network, which mainly uses multi-layer nonlinear functions to learn the mapping relationship between input data and features; the deep learning algorithm can automatically learn related features according to the target; the other is the attention mechanism, mainly through Different weights are assigned to local information, so as to obtain an expression with different proportions of local informati...

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Abstract

The invention discloses a speech classification method based on a deep neural network, and aims at solving different speech classification problems through a unified algorithm model. The method of theinvention includes the steps of S1, converting a speech into a corresponding spectrogram; segmenting the complete spectrogram along the frequency domain into blocks to obtain a local frequency domaininformation set; S2, taking the complete and local frequency domain information as inputs of a model respectively, and based on the different inputs, the convolutional neural network being capable ofextracting local and global features; S3, using an attention mechanism to fuse global and local feature expressions to form a final feature expression; S4, using tagged data to train the network by gradient descent and back propagation algorithms; and S5, using the trained parameters for an untagged speech and taking the classification of highest probability that the model outputs as a predictionresult. The method of the invention realizes a unified algorithm model for different speech classification problems, and improves the accuracy on multiple speech classification problems.

Description

technical field [0001] A speech classification method based on a deep neural network is used to process different speech classification tasks, involving speech signal processing, artificial intelligence and other technical fields. Background technique [0002] With the rapid development of computer technology, human beings are increasingly dependent and demanding on computers, how to better interact with computers has become a research hotspot. As the most common and natural way of communication in daily life, speech contains a huge amount of information, such as the speaker's accent, the speaker's emotional state, and so on. The computer's speech classification and recognition ability is an important part of the computer's speech processing and the key premise for realizing the natural human-computer interaction interface, which has great research value and application value. Speech classification technology is a very important research direction, it plays an important rol...

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Application Information

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IPC IPC(8): G10L15/02G10L15/16G06N3/04G06N3/08
CPCG06N3/084G10L15/02G10L15/16G06N3/045
Inventor 毛华章毅吴雨
Owner SICHUAN UNIV
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