Voice emotion recognition system and voice emotion recognition method

Abstract

The invention discloses a voice emotion recognition system which comprises: an audio preprocessing module, a CNN module, a pyramid FSMN module, a time step attention module and an output module, whichare connected in sequence. The invention also discloses a speech emotion recognition method applied to the speech emotion recognition system, wherein the method comprises the following steps: 1, carrying out the preliminary operation of speech, thereby obtaining a speech spectrum feature map; 2, operating the spectrogram feature map, and constructing a spectrogram feature map containing audio shallow information; 3, further processing the spectrogram feature map containing the audio shallow information to obtain deeper semantic information and context information; 4, processing the spectrogram feature map with deeper semantic information and context information to obtain a feature vector with the highest relevancy between the whole speech and the emotion of the speaker; and 5, outputtingan emotion category corresponding to the whole section of voice. Compared with the prior art, the speech emotion recognition performance of the speech emotion recognition method is greatly improved.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence and speech recognition, in particular to a speech emotion recognition system and a speech emotion recognition method, which is an end-to-end deep neural network technology, which is improved based on DFSMN. Background technique [0002] With the continuous improvement of speech recognition technology and the wide application of speech recognition equipment, human-computer interaction is becoming more and more common in people's daily life. However, most of these devices can only recognize the text-level content of human language and cannot recognize the emotional state of the speaker, while speech emotion recognition has many useful applications in human-centered services and human-computer interaction, such as intelligent service robots, automation Call centers and distance education. So far, it has attracted considerable research attention and many methods have been proposed. D...

AI Technical Summary

Problems solved by technology

However, these hand-extracted speech features are only suitable for specific tasks and have poor generalizability.

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