| 基于改进MFCC的异常声音识别算法 |
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| 引用本文： | 贺玲玲,周元.基于改进MFCC的异常声音识别算法[J].重庆工商大学学报(自然科学版),2012,29(2):52-57. |
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| 作者姓名： | 贺玲玲 周元 |
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| 作者单位： | 重庆工商大学计算机科学与信息工程学院,重庆,400067 |
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| 基金项目： | 重庆市科委重大攻关项目，重庆市教委项目 |
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| 摘 要： | 在声音识别系统中,特征参数的获取对声音识别和训练有着重要的影响;MFCC算法作为典型的声音特征参数提取方法,性能稳定,识别率高;针对MFCC算法存在较大计算量的情况,提出一种改进的特征参数提取算法MFCC_E;相比于标准的MFCC算法,MFCC_E算法减少了约50%的运算量,并且易于硬件实现;实验结果表明,MFCC_E算法与MFCC算法的识别率大致相同,而计算复杂度却小很多。
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| 关 键 词： | 声音识别 特征提取 MFCC MFCC_E GMM |
Abnormal Audio Recognition Algorithm Based on Improved MFCC |
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| HE Ling-ling,ZHOU Yuan.Abnormal Audio Recognition Algorithm Based on Improved MFCC[J].Journal of Chongqing Technology and Business University:Natural Science Edition,2012,29(2):52-57. |
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| Authors: | HE Ling-ling ZHOU Yuan |
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| Institution: | (School of Computer Science and Information Engineering, Chongqing Technology and Business University,Chongqing 400067,China) |
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| Abstract: | In audio recognition system,the acquisition of characteristic parameters has important influence on audio recognition and training.MFCC algorithm,as a typical audio characteristic parameter extraction method,has stable performance and high recognition rate.According to the situation that MFCC algorithm has larger amount of computation,a kind of improved characteristic parameter extraction algorithm,MFCC-E,was pointed out.Compared with... |
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| Keywords: | audio recognition characteristic extraction MFCC MFCC_E GMM |
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