MATLAB 语音情感识别,包含四种识别系统,分别使用KNN,SVM,神经网络,特征降维实现,每一套均可正常运行

上传者: m0_69239579 | 上传时间: 2024-04-18 14:57:05 | 文件大小: 18.55MB | 文件类型: ZIP
本资源包含了四套独立的代码实现,旨在通过不同的机器学习和深度学习技术实现语音情感识别。这些方法包括KNN(K-最近邻算法)、SVM(支持向量机)、神经网络和特征降维技术。每套实现都能够独立运行,为研究人员和开发者提供了广泛的选择以适应各种不同的应用场景。 KNN实现:利用K-最近邻算法,通过分析和比较语音样本的特征,来识别情感状态。 SVM实现:通过支持向量机模型,对语音样本的特征进行分类,以准确判断情感。 神经网络实现:采用深度学习方法,构建神经网络模型以学习和预测语音中的情感特征。 特征降维实现:使用算法降低数据维度,以提高模型的运行效率和准确率。 所有代码均使用MATLAB编写,易于理解和应用。本资源适合用于学术研究、项目开发和算法学习,特别适合对机器学习和语音处理感兴趣的研究人员和学生。 注意,其中包含了 提取特征向量以及对语音信号进行基本处理的一些函数 均包含在了KNN这套代码的wavs文件夹下,如果运行其他三套代码报错,请将这个文件夹添加到路径。这套代码是我在课程设计过程中自己使用到的代码,对于初学者很有帮助! 如果对你有帮助,还请点赞或者评论,谢谢!!

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