基于MFCC的混响效果识别研究

Reverberation Level Recognition Based on MFCC

直达声/混响声能量比(Direct-to-Reverberant Ratio,DRR)和混响时间(Reverberation Time,RT)是判断混响效果的两个重要参数。针对合成有声语音及元音EH,在给定的混响时间下,提取不同直达声/混响声能量比的混响语音信号的MFCC(Me-Frequency Cepstral Coefficients)特征,分别对其进行混响效果识别的10折交叉验证。利用高斯混合模型对训练集进行聚类分析,得到其概率分布函数,通过马氏距离(Mahalanobis Distance,MD)计算测试集的每个样本的混响效果概率,进而判断其混响效果等级。实验结果证明,合成有声语音基于MFCC的混响效果识别准确率可以达到90%以上,元音EH可以达到80%以上。

Direct-to-Reverberant energy Ratio(DRR)and Reverberation Time(RT)are the primary parameters for reverberation strength judgement.Given some selected RT,cluster reverberant synthesized voiced speech and vowel EH at different DRR based on MFCC,and use 10-fold cross validation for reverberation level recognition,respectively.Train the training dataset by Gaussian Mixture Model to obtain the probability distribution,and calculate the test dataset probability via Mahalanobis Distance in order to achieve the recognition purpose.Experiments show that reverberant voiced speech recognition accuracy is higher than 90%,and reverberant vowel EH is higher than 80%.