Speech emotion recognition equipment and speech emotion recognition method

Abstract

The invention relates to speech emotion recognition equipment and a speech emotion recognition method. The speech emotion recognition equipment comprises an analysis device, a probability calculating device and an emotion judging device, wherein the analysis device matches emotional characteristics of input speech with a plurality of emotion models so as to ensure a plurality of possible emotional states; the probability calculating device calculates the final probability of the possible emotional states in the previous emotional states of a speaker according to the knowledge of conditional probability converted among the emotional states in the speaking process of the speaker; and the emotion judging device selects a possible emotional state with the maximum final probability from the possible emotional states as the emotional state of the input speech.

Description

technical field [0001] The invention relates to speech recognition technology. More specifically, the present invention relates to speech emotion recognition devices and methods. Background technique [0002] In recent years, emotion has played an important role in human perception, decision-making and other processes. For a long time, the study of emotional intelligence existed only in the field of psychology and cognitive science. In recent years, with the development of artificial intelligence, the combination of emotional intelligence and computer technology has produced the research topic of emotional computing. This will greatly promote the development of computer technology. Automatic emotion recognition is the first step towards affective computing. Speech, as the most important communication medium for human beings, carries rich emotional information. How to automatically recognize the speaker's emotional state from speech has attracted extensive attention from...

AI Technical Summary

Problems solved by technology

Schuller B et al. believe that both prosodic features and spectral information can reflect the emotion of speech, but spectral information is more affected by phonemes and is more likely to be affected by sentence content, which is not conducive to establishing a language-independent emotion recognition system, so prosodic features are used.

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