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调查发现在语音情感检测知识

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知识发现是指寻找一些相关信息的批量的数据量。语音情感识别是基于知识发现的一个主要地区。本研究工作进行了使用四个情感即悲伤快乐愤怒和侵略性。这项研究工作具有两个部分即训练和测试的部分。培训部分将由演讲的升级文件与数据库系统。一旦上传一个文件,系统将提取的特征语音文件和一个叫做MFCC算法。MFCC算法提取特征向量的演讲文件然后最大值,最小值和平均值的特征向量将保存到数据库中。过程将重复一次又一次,直到最后一个类别是没有实现。培训部分完成后,测试部分将会启动。测试部分包括两个分类器的分类过程。 The first classifier is neural networks whose back propagation feed forward neural network would be used for the processing. The BPNN is one the most affective classifier out of the available classifiers. The initial hidden layer in the BPNN process has been kept as 20 and minimum number of iterations is 5. Some sort of previous work has been also implemented before this research work getting proposed like use of BPNN for speech classification but the combination of MFCC, BPNN for the same feature set has not been proposed yet. To show the effectiveness of the work, the same process has been repeated with Support Vector Machine and the accuracy would be measured in both the cases.

年代。Jagadeesh这位Soundappan, Dr.R.Sugumar

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