Voice emotion recognition method and device, medium and electronic equipment

Abstract

The invention relates to a voice emotion recognition method and device, a medium and electronic equipment, and belongs to the technical field of emotion recognition. The method comprises the steps: extracting various types of audio features of user voice when the user voice is received; matching the audio features with feature samples in an emotional feature library to obtain emotional labels corresponding to the feature samples matched with the audio features; constructing a feature tag matrix of the user voice based on the audio features and the emotion tags corresponding to the matched feature samples; inputting the feature tag matrix into a multi-emotion recognition model to obtain a plurality of emotion sets and scene tags corresponding to the emotion sets; and acquiring a scene tag matched with the voice scene of the user voice so as to determine an emotion set corresponding to the matched scene tag as the recognized user voice emotion. According to the invention, various potential emotions can be efficiently and accurately recognized from the voice.

Description

technical field [0001] The present application relates to the technical field of emotion recognition, in particular, to a voice emotion recognition method, device, medium and electronic equipment. Background technique [0002] Affective computing is an important technology that empowers intelligent machines to perceive, understand and express various emotional states. As an important carrier of emotional information expression, speech technology has also received more and more attention. Although the current speech emotion detection has achieved good results, most models can only judge a single emotion due to problems such as data set quality and subjective labeling of emotions, and there are few types of emotions that can be judged, so they cannot accurately describe the emotions in complex speech. Hiding emotions, and it is difficult to determine the boundaries of various emotions that may be contained in a piece of speech. These problems greatly limit the promotion and de...

AI Technical Summary

Problems solved by technology

Although the current speech emotion detection has achieved good results, most models can only judge a single emotion due to problems such as data set quality and subjective labeling of emotions, and there are few types of emotions that can be judged, so they cannot accurately describe the emotions in complex speech. Hiding emotions, and it is difficult to determine the boundaries of various emotions that may be contained in a piece of speech. These problems greatly limit the promotion and development of speech emotion recognition technology

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