Optimization method of speech emotion recognition

A speech emotion recognition and speech technology, applied in speech recognition, speech analysis, character and pattern recognition, etc., can solve the problem of low accuracy rate of speech emotion recognition, and achieve the effect of improving recognition and optimization effect.

Inactive Publication Date: 2017-12-08
HARBIN UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

[0003] China started relatively late in this research, and the correct rate of speech emotion recognition is relatively low, but the technology in speech emotion recognition is constantly catching up with the world's technological frontier, and a better method for selecting relevant parameters is urgently needed to solve speech emotion. to improve the recognition rate

Method used

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  • Optimization method of speech emotion recognition
  • Optimization method of speech emotion recognition
  • Optimization method of speech emotion recognition

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Embodiment 1

[0026] A preferred method for speech emotion recognition, the method comprises the steps of: first selecting the Berlin data set and the Chinese Academy of Sciences Chinese emotional speech database as the speech database for emotion recognition, including happy, angry, afraid, sad, calm 5 in the described speech database A test set and a training set were selected for recognition of 5 kinds of emotional speech, and then the signal extraction of characteristic parameters of the 5 kinds of emotional speech was carried out, and the method of combining the Fisher criterion and the principle of maximum entropy was used in the extracted characteristic parameter signal The SVM kernel parameters are obtained, and then the SVM kernel parameters are used to train the SVM, and finally the speech emotion signal is recognized by using the kernel parameters optimized by the SVM.

Embodiment 2

[0028] The preferred method of the speech emotion recognition described in embodiment 1, the signal extraction of the feature parameters is carried out in the speech emotion recognition using the combination of the two methods of prosodic feature and sound quality feature, and find out 3 main The characteristics are the signal law of the pitch frequency, amplitude energy and formant, and then through statistical analysis, the maximum value, minimum value, mean value and variance of the pitch frequency, amplitude energy and formant characteristics are obtained.

Embodiment 3

[0030] The preferred method of speech emotion recognition described in embodiment 1, the method that described Fisher's criterion and maximum entropy principle combine is: Fisher's criterion and the category interval of sample are related to the interval within the class, and the principle of maximum entropy is related to the degree of uniform distribution in the class , combined with the characteristics of the two to select the SVM kernel parameters.

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Abstract

The invention relates to an optimization method of speech emotion recognition. At present, speech is a tool for communication between people and for thinking and feeling expression; in order to achieve the purpose that a computer can communicate with humans as people, speech emotion recognition gradually becomes a research hot spot in the field of intelligent human-computer interaction; and in China, the research starts relatively late, and a correction rate of the speech emotion recognition is also quite low. The optimization method comprises the following steps: firstly, taking Berlin data set and Mandarin Emotional Speech Database of Chinese Academy of Sciences as speech database of emotion recognition, wherein the speech database includes five emotional speeches, namely happiness, anger, fear, sadness and calm, and recognizing the five emotional speeches so as to select out a test set and a training set; then, implementing characteristic parameter signal extraction on the five emotional speeches, and obtaining SVM kernel parameters from extracted characteristic parameter signals by virtue of a method combining Fisher criteria and the principle of maximum entropy; then, training an SVM by virtue of the SVM kernel parameters; and finally, recognizing speech emotion signals by virtue of kernel parameters which are optimized by the SVM.

Description

Technical field: [0001] The invention relates to a preferred method for speech emotion recognition. Background technique: [0002] At present, speech is a bridge between people and a tool for expressing thoughts and emotions. In order to enable computers to communicate with humans like humans, speech emotion recognition has gradually become a research hotspot in the field of intelligent human-computer interaction. Foreign scholars aim at this A lot of research has been done, such as the emotional robot researched by the MIT laboratory of the Massachusetts Institute of Technology, the blue eye project of IBM, and a flower that can perceive human emotions developed by NEC. Research has laid a good foundation. [0003] In China, this research started relatively late, and the correct rate of speech emotion recognition is relatively low, but the technology in speech emotion recognition is constantly catching up with the world's technological frontier. At present, there is an urg...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G10L25/63G10L15/02G10L15/18G06K9/62
CPCG10L15/02G10L15/1807G10L25/63G06F18/2411
Inventor 刘明珠李晓琴
Owner HARBIN UNIV OF SCI & TECH
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