Reserch And Application Of Speech Emotion Recognition Technology

In this paper,we propose a semantic combination of speech natural emotion recognition method,which uses the complementarity between speech signal and the emotion information in text information to solve the problem of emotion recognition,so as to obtain more accurate and reliable speech recognition compared with pure speech signal The recognition result.After researching and summarizing a great deal of work in the related fields,this paper presents a sentiment model based on two sentiment models,the sentiment and discrete sentiment.Based on this,a semantic and semantic Acoustic Features Combined with Speech Emotion Recognition Model.Among them,SVM(Support Vector Machine)is used as the basic recognition model of voice acoustic feature channel,and emotion recognition based on affective dictionary is used as text channel.Two textual affective tendencies are set: positive and negative,The recognition results are weighted by two-channel multi-channel fusion to construct a semantic combined emotion recognition model.In the process of building the system,this paper refers to the Chinese speech emotion database built by the Shenzhen Institute of Advanced Science of the Chinese Academy of Sciences around the intelligent center and organizes it t o realize the establishment of the emotional speech database.Based on the emotion-discretization model based on dimensions,an emotion recognition system based on phonetic acoustic features is constructed firstly.The system has the functions of endpoint detection,feature extraction,classifier training and recognition.By multiple classification in different dimensions,the system can not only effectively increase the amount of training data,but also improve the recognition rate on the data set,Semanti c recognition methods combine to create a more accurate emotional recognition model.Based on the establishment of the emotion recognition system,this dissertation also proposes a semantic combined speech emotion recognition method based on the dimension emotional discretization model.By using the existing speech recognition algorithm to recognize the emotion speech,the emotion dictionary can query the emotion value of the sentence to obtain the emotion labeling of the emotion word in the process of recognizing the meaning of the sentence,and to recognize the semantic of the text emotionally.Gain emotional orientation in different dimensions.Finally,multi-channel multi-channel fusion algorithm is applied to multi-channel fusion of speech recognition r esults and semantic emotion recognition results in the direction of emotional orientation.Finally,the multi-channel fusion weight is determined through multiple experiments and the result is reached A certain degree of recognition of the rate of improvem ent,so as to achieve a semantic combination of optimization model.