期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2014
卷号：2
期号：5
出版社：S&S Publications
摘要：Knowledge discovery refers to finding some relevant information out of a bulk amount of data. Speech emotionrecognition is one of the major areas in the knowledge based discovery. This research work has been carried out using fouremotions namely sad happy angry and aggressive. This research work possesses two sections namely training and thetesting part. The training part will consists of the updation of the speech files with the data base system. Once a file isuploaded, the system would extract the features of the speech file with an algorithm named MFCC. The MFCC algorithmwould extract a feature vector out the speech file and then the maximum, minimum and average value of the feature vectorwould be saved into the database. The process would repeat itself again and again till the last category is not achieved.Once the training part is complete, the testing section would be initiated. The testing section would involve theclassification process in which two classifiers would be used. The first classifier is neural networks whose back propagationfeed forward neural network would be used for the processing. The BPNN is one the most affective classifier out of theavailable classifiers. The initial hidden layer in the BPNN process has been kept as 20 and minimum number of iterations is5. Some sort of previous work has been also implemented before this research work getting proposed like use of BPNN forspeech classification but the combination of MFCC, BPNN for the same feature set has not been proposed yet. To show theeffectiveness of the work, the same process has been repeated with Support Vector Machine and the accuracy would bemeasured in both the cases.
